suppressPackageStartupMessages({
library(tidyverse)
library(readr)
library(lme4)
library(lmerTest)
library(emmeans)
library(dplyr)
library(tidyr)
library(ggplot2)
library(patchwork)
library(car) # Type II/III ANOVA
})
# Lighter-weight df method for emmeans on lmer (avoids huge memory from KR/Satt)
emm_options(lmer.df = "asymptotic")
options(
dplyr.summarise.inform = FALSE,
contrasts = c("contr.sum", "contr.poly")
)
# Axis labels helper
axis_labels <- c(x = "X", y = "Y", z = "Z")
data_dir <- "/Users/can/Documents/Uni/Thesis/Data/...v/merged/Cleaned"
# Step counts per block (nominal)
step_counts <- tibble(
Block = c(1, 2, 3, 4, 5),
Steps = c(6, 12, 18, 18, 18)
)
# binary Accuracy factor from trial.acc (1 -> 1, else -> 0)
mk_accuracy <- function(df) {
df %>% mutate(Accuracy = factor(if_else(trial.acc == 1, 1L, 0L), levels = c(0, 1)))
}
normalize_ids <- function(df) {
df %>%
mutate(
subject = if ("subject" %in% names(.)) subject else Subject,
Block = as.integer(Block),
trial = if ("trial" %in% names(.)) trial else Trial
) %>%
mutate(trial_id = interaction(subject, Block, trial, drop = TRUE))
}
assign_steps_by_block <- function(df, steps_df = step_counts) {
df %>%
inner_join(steps_df, by = "Block") %>%
group_by(subject, Block, trial) %>%
mutate(Step = cut_number(row_number(), n = unique(Steps), labels = FALSE)) %>%
ungroup()
}
# Tag trial phases using Marker.Text: start (27), end (26 or 25). Preparation = 1500 ms pre-start
# Requires columns: subject, Block, trial, ms, Marker.Text
tag_trial_phases <- function(df) {
df %>%
group_by(subject, Block, trial) %>%
mutate(
start_ms = ms[which(Marker.Text == 27)[1]],
end_ms = {
end_candidates <- which(Marker.Text %in% c(26, 25))
if (length(end_candidates) > 0) ms[end_candidates[1]] else NA_real_
},
phase = case_when(
!is.na(start_ms) & !is.na(end_ms) & ms >= start_ms & ms <= end_ms ~ "Execution",
!is.na(start_ms) & ms >= (start_ms - 1500) & ms < start_ms ~ "Preparation",
TRUE ~ NA_character_
)
) %>%
ungroup() %>%
filter(!is.na(phase))
}
# Compute RMS per phase (Preparation / Execution) per subject × Block × trial
compute_phase_rms <- function(df) {
df %>%
group_by(subject, Block, trial, phase) %>%
summarise(
rms_x = sqrt(mean(CoM.acc.x^2, na.rm = TRUE)),
rms_y = sqrt(mean(CoM.acc.y^2, na.rm = TRUE)),
rms_z = sqrt(mean(CoM.acc.z^2, na.rm = TRUE)),
.groups = "drop"
)
}
# Detect per-step onsets (Marker.Text in {14,15,16,17}) and compute 7-sample window RMS (±3)
# Returns one row per detected step onset per trial with RMS per axis
compute_stepwise_rms <- function(tagged_exec_df, max_steps_keep = 18) {
step_markers <- c(14L, 15L, 16L, 17L)
# Keep only execution rows
exec <- tagged_exec_df %>% filter(phase == "Execution") %>% arrange(subject, Block, trial, ms)
# Detect step onset rows within each trial
exec_mark <- exec %>%
group_by(subject, Block, trial) %>%
mutate(
in_step = Marker.Text %in% step_markers,
onset = in_step & (is.na(lag(in_step)) | !lag(in_step) | (Marker.Text != lag(Marker.Text)))
) %>%
filter(onset) %>%
mutate(step_index = row_number()) %>%
ungroup()
# If there are no onsets, return empty tibble
if (nrow(exec_mark) == 0) return(tibble())
# Per-trial total step count
step_counts_lookup <- exec_mark %>%
group_by(subject, Block, trial) %>%
summarise(step_count = max(step_index), .groups = "drop")
# Join row indices to full exec to build windows
exec_with_row <- exec %>% group_by(subject, Block, trial) %>% mutate(row_id = row_number()) %>% ungroup()
onset_idx <- exec_mark %>% select(subject, Block, trial, ms, step_index) %>%
left_join(exec_with_row %>% select(subject, Block, trial, ms, row_id), by = c("subject", "Block", "trial", "ms"))
# Build ±3 row windows around each onset row and compute RMS
win <- purrr::map_dfr(seq_len(nrow(onset_idx)), function(i) {
r <- onset_idx$row_id[i]
s <- onset_idx$step_index[i]
grp <- onset_idx[i, c("subject", "Block", "trial")]
tmp <- exec_with_row %>%
dplyr::semi_join(grp, by = c("subject", "Block", "trial")) %>%
dplyr::filter(row_id >= (r - 3), row_id <= (r + 3))
if (nrow(tmp) == 0) return(NULL)
tibble(
subject = grp$subject, Block = grp$Block, trial = grp$trial,
Step = s,
RMS = c(
sqrt(mean(tmp$CoM.acc.x^2, na.rm = TRUE)),
sqrt(mean(tmp$CoM.acc.y^2, na.rm = TRUE)),
sqrt(mean(tmp$CoM.acc.z^2, na.rm = TRUE))
),
Axis = factor(c("x", "y", "z"), levels = c("x", "y", "z"))
)
})
# Keep first N steps per trial and add step_count
win %>%
group_by(subject, Block, trial) %>%
filter(Step <= max_steps_keep) %>%
ungroup() %>%
left_join(step_counts_lookup, by = c("subject", "Block", "trial"))
}
# Join trial-level Accuracy to a summary table (by subject × Block × trial)
add_accuracy_to <- function(df_core, df_lookup) {
# Build accuracy lookup with consistent key types (character) to avoid factor/int join issues
acc_tbl <- df_lookup %>%
distinct(subject, Block, trial, trial.acc) %>%
mk_accuracy() %>%
transmute(
subject = as.character(subject),
Block = as.character(Block),
trial = as.character(trial),
Accuracy
)
df_core %>%
mutate(
subject = as.character(subject),
Block = as.character(Block),
trial = as.character(trial)
) %>%
left_join(acc_tbl, by = c("subject", "Block", "trial")) %>%
# Convert Block/trial back to numeric where appropriate
mutate(
Block = type.convert(Block, as.is = TRUE),
trial = type.convert(trial, as.is = TRUE)
)
}
# Generic LMM runner for phase × block per axis
run_phase_block_models <- function(rms_combined) {
for (axis in c("x", "y", "z")) {
cat("
=============================
")
cat(paste("Axis:", toupper(axis), "
"))
cat("=============================
")
axis_col <- paste0("rms_", axis)
# Trim to needed columns to reduce memory footprint
df_axis <- rms_combined %>%
dplyr::select(subject, Block, Trial, phase, Accuracy, !!sym(axis_col)) %>%
droplevels()
fml <- as.formula(paste(axis_col, "~ Block * phase + Accuracy + (1 | subject) + (1 | Trial)"))
model <- lmer(fml, data = df_axis)
cat("
Model Summary:
"); print(summary(model))
emms <- emmeans(model, ~ Block * phase)
cat("
Estimated Marginal Means (df=asymptotic):
"); print(summary(emms))
cat("
Type II ANOVA (Chisq):
"); print(car::Anova(model, type = 2, test.statistic = "Chisq"))
cat("
Pairwise (within phase; Tukey):
")
pw <- contrast(emms, interaction = c("revpairwise"), by = "phase", adjust = "tukey")
print(pw)
rm(model, emms, df_axis); gc()
}
}
# Generic LMM runner for stepwise RMS per block/axis with Accuracy
run_step_models <- function(step_df, block, n_steps) {
d <- step_df %>% filter(Block == block, Step <= n_steps)
for (ax in c("x", "y", "z")) {
dd <- d %>% filter(Axis == ax)
if (nrow(dd) == 0) next
cat("\n\n--- Block", block, "Axis", toupper(ax), "---\n")
m <- lmer(RMS ~ Step + Accuracy + (1 | subject) + (1 | trial_id), data = dd)
print(car::Anova(m, type = 2, test.statistic = "Chisq"))
e <- emmeans(m, ~ Step)
cat("Estimated Marginal Means:\n"); print(summary(e))
cat("Pairwise (Tukey):\n"); print(contrast(e, method = "pairwise", adjust = "tukey"))
}
}
# Simple bar plot function: mean ± SE by Step × Block, faceted by Axis
plot_step_bars <- function(step_df, title_prefix = "") {
se <- function(x) sd(x, na.rm = TRUE) / sqrt(sum(!is.na(x)))
sum_df <- step_df %>% group_by(Block, Step, Axis) %>% summarise(mean_RMS = mean(RMS, na.rm = TRUE), se_RMS = se(RMS), .groups = "drop")
ggplot(sum_df, aes(x = Step, y = mean_RMS, fill = factor(Block))) +
geom_col(position = position_dodge(width = 0.8)) +
geom_errorbar(aes(ymin = mean_RMS - se_RMS, ymax = mean_RMS + se_RMS), width = 0.2, position = position_dodge(width = 0.8)) +
facet_wrap(~ Axis, nrow = 1, labeller = as_labeller(axis_labels)) +
labs(title = paste0(title_prefix, " Step-wise RMS (mean ± SE)"), x = "Step", y = "RMS") +
theme_minimal()
}Motion Analysis only
# Gather mixed files
mixed_files <- list.files("/Users/can/Documents/Uni/Thesis/Data/Xsens/cleaned_csv/merged/Cleaned", pattern = "_final\\.csv$", full.names = TRUE)
all_data_mixed <- map_dfr(mixed_files, read_csv)Rows: 360534 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 379431 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 340045 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 342328 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 386760 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 355905 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 336982 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 434486 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 441207 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 368716 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 487396 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 435226 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 324591 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 372054 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 392294 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 412795 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 356869 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
Rows: 350365 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (21): Frame, CoM.pos.x, CoM.pos.y, CoM.pos.z, CoM.vel.x, CoM.vel.y, CoM....
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.# Merge
all_data_mixed <- map_dfr(mixed_files, read_csv, show_col_types = FALSE) %>% normalize_ids() %>% mk_accuracy()
# Trial phases once
tagged_data <- tag_trial_phases(all_data_mixed) %>% mutate(DataType = "Mixed")
tagged_data2 <- tagged_data#Build step-wise table
# Helper: robust step-onset finder for Execution phase (uses Marker.Text)
.build_exec_step_onsets <- function(df) {
exec <- df %>% dplyr::filter(phase == "Execution")
exec_step <- exec %>%
dplyr::filter(
!is.na(Marker.Text),
suppressWarnings(!is.na(as.integer(Marker.Text))),
as.integer(Marker.Text) >= 1,
as.integer(Marker.Text) <= 18
) %>%
dplyr::mutate(
Step = as.integer(Marker.Text),
# create trial_id if missing
trial_id = if ("trial_id" %in% names(.)) trial_id else interaction(subject, Block, trial, drop = TRUE)
) %>%
# NOTE: do NOT select `Trial` (capital T); your data has `trial` (lowercase)
dplyr::select(subject, Block, trial, phase, ms, Step, trial_id)
exec_step
}
.assign_exec_steps_evenly <- function(df) {
df %>%
dplyr::filter(phase == "Execution") %>%
assign_steps_by_block() %>% # uses your existing helper + step_counts
dplyr::mutate(
trial_id = if ("trial_id" %in% names(.)) trial_id else interaction(subject, Block, trial, drop = TRUE)
) %>%
dplyr::select(subject, Block, trial, phase, ms, Step, trial_id)
}
# Try onsets first, else fallback
sw_all <- .build_exec_step_onsets(tagged_data)
if (nrow(sw_all) == 0) {
message("No explicit step-onset markers found; assigning steps evenly within trials.")
sw_all <- .assign_exec_steps_evenly(tagged_data)
}
# Per-trial step count (for mixed lengths in Blocks 4–5)
sw_all <- sw_all %>%
dplyr::group_by(subject, Block, trial) %>%
dplyr::mutate(step_count = max(Step, na.rm = TRUE)) %>%
dplyr::ungroup()
sw_all <- sw_all %>%
dplyr::select(subject, Block, trial, phase, Step, step_count, trial_id)data preprocessing and creating models
trial_acc_summary <- tagged_data %>%
select(subject, Block, trial, trial.acc) %>%
distinct() %>%
filter(trial.acc == 1) %>%
group_by(subject, Block) %>%
summarise(n_trials_with_acc1 = n(), .groups = "drop") %>%
group_by(Block) %>%
summarise(
mean_trials_with_acc1 = mean(n_trials_with_acc1),
sd_trials_with_acc1 = sd(n_trials_with_acc1),
n_subjects = n()
)
print(trial_acc_summary)# A tibble: 5 × 4
Block mean_trials_with_acc1 sd_trials_with_acc1 n_subjects
<int> <dbl> <dbl> <int>
1 1 40.2 3.13 18
2 2 34.2 7.19 18
3 3 27.8 9.85 18
4 4 39.2 4.51 18
5 5 28.9 10.0 18# Phase RMS
rms_data <- compute_phase_rms(tagged_data)
exec_data <- rms_data %>% filter(phase == "Execution")
for (axis in c("x", "y", "z")) {
axis_col <- paste0("rms_", axis)
print(
ggplot(exec_data, aes(x = factor(Block), y = .data[[axis_col]], fill = phase)) +
geom_boxplot(alpha = 0.7, outlier.shape = NA) +
geom_jitter(width = 0.2, alpha = 0.4, size = 0.6) +
geom_vline(xintercept = 3.5, linetype = "dashed") +
coord_cartesian(ylim = c(0, 2.5)) +
labs(title = paste("Execution Phase:", toupper(axis), "Axis"), x = "Block", y = "RMS") +
theme_minimal()
)
}
prep_data <- tagged_data %>% filter(phase == "Preparation")
prep_rms <- compute_phase_rms(prep_data)
for (axis in c("x", "y", "z")) {
axis_col <- paste0("rms_", axis)
print(
ggplot(prep_rms, aes(x = factor(Block), y = .data[[axis_col]], fill = phase)) +
geom_boxplot(alpha = 0.7, outlier.shape = NA) +
geom_jitter(width = 0.2, alpha = 0.4, size = 0.6) +
geom_vline(xintercept = 3.5, linetype = "dashed") +
coord_cartesian(ylim = c(0, 0.5)) +
labs(title = paste("Preparation Phase:", toupper(axis), "Axis"), x = "Block", y = "RMS") +
theme_minimal()
)
}
# Combine prep + exec, join trial Accuracy, then model per axis
rms_combined <- bind_rows(prep_rms, exec_data) %>%
# Join Accuracy before converting key columns to factors
add_accuracy_to(all_data_mixed) %>%
mutate(
phase = factor(phase, levels = c("Preparation", "Execution")),
Block = factor(Block),
Trial = factor(trial)
)Warning in left_join(., acc_tbl, by = c("subject", "Block", "trial")): Detected an unexpected many-to-many relationship between `x` and `y`.
ℹ Row 1 of `x` matches multiple rows in `y`.
ℹ Row 3021 of `y` matches multiple rows in `x`.
ℹ If a many-to-many relationship is expected, set `relationship =
"many-to-many"` to silence this warning.run_phase_block_models(rms_combined)
=============================
Axis: X
=============================
Model Summary:
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: fml
Data: df_axis
REML criterion at convergence: 1156.2
Scaled residuals:
Min 1Q Median 3Q Max
-4.2686 -0.5173 -0.0979 0.3264 8.9700
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.0002199 0.01483
subject (Intercept) 0.0170146 0.13044
Residual 0.0635587 0.25211
Number of obs: 11552, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 4.028e-01 3.091e-02 1.718e+01 13.030 2.47e-10 ***
Block1 3.041e-02 5.062e-03 1.152e+04 6.007 1.95e-09 ***
Block2 1.660e-02 4.709e-03 1.150e+04 3.525 0.000426 ***
Block3 -2.104e-02 4.733e-03 1.147e+04 -4.446 8.84e-06 ***
Block4 2.224e-02 4.743e-03 1.150e+04 4.689 2.77e-06 ***
phase1 -2.881e-01 2.357e-03 1.149e+04 -122.230 < 2e-16 ***
Accuracy1 -1.782e-02 2.499e-03 1.086e+04 -7.132 1.05e-12 ***
Block1:phase1 -9.185e-02 4.974e-03 1.148e+04 -18.467 < 2e-16 ***
Block2:phase1 -1.717e-02 4.703e-03 1.147e+04 -3.651 0.000262 ***
Block3:phase1 6.341e-02 4.685e-03 1.147e+04 13.535 < 2e-16 ***
Block4:phase1 -1.417e-02 4.719e-03 1.147e+04 -3.003 0.002681 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2 Block3 Block4 phase1 Accrc1 Blc1:1 Blc2:1
Block1 0.006
Block2 0.000 -0.268
Block3 -0.001 -0.285 -0.245
Block4 0.001 -0.254 -0.248 -0.255
phase1 -0.001 -0.013 0.002 0.003 0.003
Accuracy1 0.008 0.175 -0.001 -0.107 0.082 -0.005
Block1:phs1 -0.001 -0.033 0.009 0.009 0.008 0.072 -0.003
Block2:phs1 0.000 0.009 -0.015 0.002 0.002 -0.002 -0.001 -0.272
Block3:phs1 0.000 0.009 0.002 -0.014 0.002 -0.008 0.001 -0.271 -0.247
Block4:phs1 0.000 0.009 0.002 0.001 -0.012 0.002 0.003 -0.273 -0.250
Blc3:1
Block1
Block2
Block3
Block4
phase1
Accuracy1
Block1:phs1
Block2:phs1
Block3:phs1
Block4:phs1 -0.248
Estimated Marginal Means (df=asymptotic):
Block phase emmean SE df asymp.LCL asymp.UCL
1 Preparation 0.0533 0.0318 Inf -0.00911 0.116
2 Preparation 0.1141 0.0317 Inf 0.05201 0.176
3 Preparation 0.1571 0.0317 Inf 0.09496 0.219
4 Preparation 0.1228 0.0317 Inf 0.06062 0.185
5 Preparation 0.1263 0.0316 Inf 0.06436 0.188
1 Execution 0.8131 0.0319 Inf 0.75060 0.876
2 Execution 0.7246 0.0317 Inf 0.66248 0.787
3 Execution 0.6064 0.0317 Inf 0.54426 0.669
4 Execution 0.7273 0.0317 Inf 0.66510 0.789
5 Execution 0.5829 0.0316 Inf 0.52094 0.645
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Type II ANOVA (Chisq):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: rms_x
Chisq Df Pr(>Chisq)
Block 148.880 4 < 2.2e-16 ***
phase 14600.810 1 < 2.2e-16 ***
Accuracy 50.864 1 9.897e-13 ***
Block:phase 574.253 4 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Pairwise (within phase; Tukey):
phase = Preparation:
Block_revpairwise estimate SE df z.ratio p.value
2 - 1 0.06087 0.0108 Inf 5.628 <.0001
3 - 1 0.10381 0.0109 Inf 9.564 <.0001
3 - 2 0.04295 0.0104 Inf 4.114 0.0004
4 - 1 0.06951 0.0108 Inf 6.423 <.0001
4 - 2 0.00865 0.0105 Inf 0.825 0.9231
4 - 3 -0.03430 0.0105 Inf -3.267 0.0096
5 - 1 0.07301 0.0106 Inf 6.905 <.0001
5 - 2 0.01214 0.0101 Inf 1.198 0.7524
5 - 3 -0.03081 0.0101 Inf -3.053 0.0192
5 - 4 0.00349 0.0102 Inf 0.343 0.9970
phase = Execution:
Block_revpairwise estimate SE df z.ratio p.value
2 - 1 -0.08848 0.0111 Inf -7.966 <.0001
3 - 1 -0.20671 0.0111 Inf -18.548 <.0001
3 - 2 -0.11822 0.0106 Inf -11.174 <.0001
4 - 1 -0.08584 0.0111 Inf -7.733 <.0001
4 - 2 0.00264 0.0106 Inf 0.249 0.9992
4 - 3 0.12087 0.0106 Inf 11.377 <.0001
5 - 1 -0.23025 0.0109 Inf -21.217 <.0001
5 - 2 -0.14176 0.0103 Inf -13.821 <.0001
5 - 3 -0.02354 0.0102 Inf -2.305 0.1431
5 - 4 -0.14441 0.0103 Inf -14.007 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 5 estimates
=============================
Axis: Y
=============================
Model Summary:
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: fml
Data: df_axis
REML criterion at convergence: 4871.2
Scaled residuals:
Min 1Q Median 3Q Max
-3.7322 -0.5187 -0.0835 0.3331 23.4331
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.0001537 0.0124
subject (Intercept) 0.0214834 0.1466
Residual 0.0877958 0.2963
Number of obs: 11552, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 4.218e-01 3.471e-02 1.710e+01 12.152 7.70e-10 ***
Block1 3.571e-02 5.948e-03 1.152e+04 6.005 1.97e-09 ***
Block2 2.512e-02 5.534e-03 1.151e+04 4.539 5.70e-06 ***
Block3 -2.054e-02 5.556e-03 1.142e+04 -3.697 0.000219 ***
Block4 1.555e-02 5.574e-03 1.151e+04 2.789 0.005290 **
phase1 -3.046e-01 2.770e-03 1.150e+04 -109.975 < 2e-16 ***
Accuracy1 -1.736e-02 2.929e-03 1.044e+04 -5.925 3.22e-09 ***
Block1:phase1 -9.992e-02 5.845e-03 1.148e+04 -17.094 < 2e-16 ***
Block2:phase1 -1.923e-02 5.528e-03 1.147e+04 -3.480 0.000504 ***
Block3:phase1 7.315e-02 5.506e-03 1.148e+04 13.284 < 2e-16 ***
Block4:phase1 -1.343e-02 5.547e-03 1.147e+04 -2.422 0.015466 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2 Block3 Block4 phase1 Accrc1 Blc1:1 Blc2:1
Block1 0.007
Block2 0.000 -0.268
Block3 -0.001 -0.285 -0.245
Block4 0.001 -0.254 -0.248 -0.255
phase1 -0.002 -0.013 0.002 0.003 0.003
Accuracy1 0.008 0.175 -0.001 -0.108 0.082 -0.006
Block1:phs1 -0.001 -0.033 0.009 0.009 0.008 0.072 -0.004
Block2:phs1 0.000 0.009 -0.015 0.002 0.002 -0.002 -0.001 -0.272
Block3:phs1 0.000 0.009 0.002 -0.014 0.002 -0.008 0.001 -0.271 -0.247
Block4:phs1 0.000 0.009 0.002 0.001 -0.012 0.002 0.003 -0.273 -0.250
Blc3:1
Block1
Block2
Block3
Block4
phase1
Accuracy1
Block1:phs1
Block2:phs1
Block3:phs1
Block4:phs1 -0.248
Estimated Marginal Means (df=asymptotic):
Block phase emmean SE df asymp.LCL asymp.UCL
1 Preparation 0.053 0.0358 Inf -0.0173 0.123
2 Preparation 0.123 0.0357 Inf 0.0531 0.193
3 Preparation 0.170 0.0357 Inf 0.0999 0.240
4 Preparation 0.119 0.0357 Inf 0.0493 0.189
5 Preparation 0.121 0.0355 Inf 0.0511 0.190
1 Execution 0.862 0.0359 Inf 0.7916 0.932
2 Execution 0.771 0.0357 Inf 0.7007 0.841
3 Execution 0.633 0.0357 Inf 0.5627 0.703
4 Execution 0.755 0.0357 Inf 0.6853 0.825
5 Execution 0.611 0.0356 Inf 0.5414 0.681
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Type II ANOVA (Chisq):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: rms_y
Chisq Df Pr(>Chisq)
Block 138.607 4 < 2.2e-16 ***
phase 11822.323 1 < 2.2e-16 ***
Accuracy 35.108 1 3.12e-09 ***
Block:phase 485.928 4 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Pairwise (within phase; Tukey):
phase = Preparation:
Block_revpairwise estimate SE df z.ratio p.value
2 - 1 0.07009 0.0127 Inf 5.515 <.0001
3 - 1 0.11681 0.0128 Inf 9.161 <.0001
3 - 2 0.04672 0.0123 Inf 3.810 0.0013
4 - 1 0.06632 0.0127 Inf 5.215 <.0001
4 - 2 -0.00377 0.0123 Inf -0.306 0.9981
4 - 3 -0.05049 0.0123 Inf -4.093 0.0004
5 - 1 0.06780 0.0124 Inf 5.457 <.0001
5 - 2 -0.00229 0.0119 Inf -0.192 0.9997
5 - 3 -0.04901 0.0119 Inf -4.134 0.0003
5 - 4 0.00148 0.0120 Inf 0.124 0.9999
phase = Execution:
Block_revpairwise estimate SE df z.ratio p.value
2 - 1 -0.09128 0.0131 Inf -6.992 <.0001
3 - 1 -0.22932 0.0131 Inf -17.516 <.0001
3 - 2 -0.13804 0.0124 Inf -11.105 <.0001
4 - 1 -0.10665 0.0130 Inf -8.176 <.0001
4 - 2 -0.01537 0.0125 Inf -1.233 0.7321
4 - 3 0.12266 0.0125 Inf 9.828 <.0001
5 - 1 -0.25091 0.0128 Inf -19.675 <.0001
5 - 2 -0.15964 0.0121 Inf -13.243 <.0001
5 - 3 -0.02160 0.0120 Inf -1.800 0.3734
5 - 4 -0.14426 0.0121 Inf -11.907 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 5 estimates
=============================
Axis: Z
=============================
Model Summary:
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: fml
Data: df_axis
REML criterion at convergence: 16049.5
Scaled residuals:
Min 1Q Median 3Q Max
-3.8020 -0.5578 -0.1423 0.3881 11.5638
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.000956 0.03092
subject (Intercept) 0.061226 0.24744
Residual 0.230927 0.48055
Number of obs: 11552, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 6.666e-01 5.867e-02 1.721e+01 11.362 2.01e-09 ***
Block1 2.016e-02 9.651e-03 1.152e+04 2.089 0.03674 *
Block2 3.803e-02 8.977e-03 1.150e+04 4.237 2.29e-05 ***
Block3 -1.560e-02 9.024e-03 1.148e+04 -1.729 0.08389 .
Block4 3.704e-02 9.042e-03 1.150e+04 4.097 4.22e-05 ***
phase1 -5.173e-01 4.493e-03 1.149e+04 -115.147 < 2e-16 ***
Accuracy1 -3.789e-02 4.767e-03 1.099e+04 -7.947 2.09e-15 ***
Block1:phase1 -1.277e-01 9.481e-03 1.148e+04 -13.470 < 2e-16 ***
Block2:phase1 -2.512e-02 8.965e-03 1.147e+04 -2.802 0.00509 **
Block3:phase1 1.002e-01 8.930e-03 1.147e+04 11.217 < 2e-16 ***
Block4:phase1 -3.600e-02 8.996e-03 1.147e+04 -4.002 6.31e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2 Block3 Block4 phase1 Accrc1 Blc1:1 Blc2:1
Block1 0.006
Block2 0.000 -0.268
Block3 -0.001 -0.285 -0.245
Block4 0.001 -0.254 -0.248 -0.255
phase1 -0.001 -0.013 0.002 0.003 0.003
Accuracy1 0.008 0.175 -0.001 -0.107 0.081 -0.004
Block1:phs1 -0.001 -0.033 0.009 0.009 0.008 0.072 -0.003
Block2:phs1 0.000 0.009 -0.015 0.002 0.002 -0.002 -0.001 -0.272
Block3:phs1 0.000 0.009 0.002 -0.014 0.002 -0.008 0.001 -0.271 -0.247
Block4:phs1 0.000 0.009 0.002 0.001 -0.012 0.002 0.003 -0.273 -0.250
Blc3:1
Block1
Block2
Block3
Block4
phase1
Accuracy1
Block1:phs1
Block2:phs1
Block3:phs1
Block4:phs1 -0.248
Estimated Marginal Means (df=asymptotic):
Block phase emmean SE df asymp.LCL asymp.UCL
1 Preparation 0.0418 0.0604 Inf -0.0766 0.160
2 Preparation 0.1622 0.0602 Inf 0.0443 0.280
3 Preparation 0.2339 0.0602 Inf 0.1160 0.352
4 Preparation 0.1504 0.0602 Inf 0.0324 0.268
5 Preparation 0.1583 0.0600 Inf 0.0408 0.276
1 Execution 1.3318 0.0606 Inf 1.2131 1.451
2 Execution 1.2471 0.0602 Inf 1.1291 1.365
3 Execution 1.0682 0.0602 Inf 0.9502 1.186
4 Execution 1.2570 0.0602 Inf 1.1390 1.375
5 Execution 1.0157 0.0600 Inf 0.8981 1.133
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Type II ANOVA (Chisq):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: rms_z
Chisq Df Pr(>Chisq)
Block 97.924 4 < 2.2e-16 ***
phase 13038.956 1 < 2.2e-16 ***
Accuracy 63.158 1 1.908e-15 ***
Block:phase 348.635 4 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Pairwise (within phase; Tukey):
phase = Preparation:
Block_revpairwise estimate SE df z.ratio p.value
2 - 1 0.12046 0.0206 Inf 5.843 <.0001
3 - 1 0.19211 0.0207 Inf 9.284 <.0001
3 - 2 0.07166 0.0199 Inf 3.601 0.0029
4 - 1 0.10858 0.0206 Inf 5.263 <.0001
4 - 2 -0.01188 0.0200 Inf -0.594 0.9760
4 - 3 -0.08353 0.0200 Inf -4.173 0.0003
5 - 1 0.11655 0.0202 Inf 5.783 <.0001
5 - 2 -0.00391 0.0193 Inf -0.202 0.9996
5 - 3 -0.07556 0.0192 Inf -3.928 0.0008
5 - 4 0.00797 0.0195 Inf 0.410 0.9941
phase = Execution:
Block_revpairwise estimate SE df z.ratio p.value
2 - 1 -0.08471 0.0212 Inf -4.001 0.0006
3 - 1 -0.26363 0.0212 Inf -12.409 <.0001
3 - 2 -0.17892 0.0202 Inf -8.871 <.0001
4 - 1 -0.07481 0.0212 Inf -3.536 0.0037
4 - 2 0.00990 0.0202 Inf 0.489 0.9884
4 - 3 0.18882 0.0203 Inf 9.323 <.0001
5 - 1 -0.31614 0.0207 Inf -15.283 <.0001
5 - 2 -0.23143 0.0196 Inf -11.837 <.0001
5 - 3 -0.05251 0.0195 Inf -2.698 0.0543
5 - 4 -0.24133 0.0197 Inf -12.281 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 5 estimates # Descriptive means/SDs by phase × block
rms_summary_blockwise <- rms_combined %>%
group_by(phase, Block) %>%
summarise(
mean_rms_x = mean(rms_x, na.rm = TRUE), sd_rms_x = sd(rms_x, na.rm = TRUE),
mean_rms_y = mean(rms_y, na.rm = TRUE), sd_rms_y = sd(rms_y, na.rm = TRUE),
mean_rms_z = mean(rms_z, na.rm = TRUE), sd_rms_z = sd(rms_z, na.rm = TRUE),
.groups = "drop"
)
print(rbind(head(rms_summary_blockwise, 6)))# A tibble: 6 × 8
phase Block mean_rms_x sd_rms_x mean_rms_y sd_rms_y mean_rms_z sd_rms_z
<fct> <fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Preparation 1 0.0642 0.0635 0.0635 0.0634 0.0616 0.0918
2 Preparation 2 0.117 0.266 0.125 0.302 0.167 0.493
3 Preparation 3 0.150 0.241 0.161 0.269 0.220 0.456
4 Preparation 4 0.127 0.223 0.121 0.220 0.160 0.376
5 Preparation 5 0.119 0.172 0.113 0.163 0.145 0.302
6 Execution 1 0.822 0.399 0.870 0.502 1.35 0.770 # Collapsed across blocks (phase only)
rms_summary_phaseonly <- rms_combined %>%
group_by(phase) %>%
summarise(
mean_rms_x = mean(rms_x, na.rm = TRUE), sd_rms_x = sd(rms_x, na.rm = TRUE),
mean_rms_y = mean(rms_y, na.rm = TRUE), sd_rms_y = sd(rms_y, na.rm = TRUE),
mean_rms_z = mean(rms_z, na.rm = TRUE), sd_rms_z = sd(rms_z, na.rm = TRUE),
.groups = "drop"
)
print(rms_summary_phaseonly)# A tibble: 2 × 7
phase mean_rms_x sd_rms_x mean_rms_y sd_rms_y mean_rms_z sd_rms_z
<fct> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Preparation 0.117 0.209 0.118 0.223 0.153 0.377
2 Execution 0.684 0.357 0.718 0.425 1.17 0.683# Build a per-trial sequence length lookup from step-wise data if available; otherwise fall back to NA
if (exists("sw_all")) {
seq_lookup <- sw_all %>%
dplyr::filter(Block %in% c(4, 5) | Block %in% c("4","5")) %>%
dplyr::group_by(subject, Block, trial) %>%
dplyr::summarise(step_count = max(Step, na.rm = TRUE), .groups = "drop") %>%
dplyr::mutate(
SeqLen = dplyr::case_when(
step_count == 6 ~ "6-step",
step_count == 12 ~ "12-step",
step_count == 18 ~ "18-step",
TRUE ~ NA_character_
)
) %>%
dplyr::transmute(subject, Block, trial, SeqLen)
} else {
seq_lookup <- rms_data %>%
dplyr::filter(Block %in% c(4, 5) | Block %in% c("4","5")) %>%
dplyr::distinct(subject, Block, trial) %>%
dplyr::mutate(SeqLen = NA_character_)
}
prep_b45 <- rms_data %>%
dplyr::filter(phase == "Preparation", Block %in% c(4, 5) | Block %in% c("4","5")) %>%
dplyr::left_join(seq_lookup, by = c("subject","Block","trial")) %>%
tidyr::pivot_longer(dplyr::starts_with("rms_"), names_to = "Axis", values_to = "RMS") %>%
dplyr::mutate(Axis = toupper(sub("^rms_", "", Axis)))
exec_b45 <- rms_data %>%
dplyr::filter(phase == "Execution", Block %in% c(4, 5) | Block %in% c("4","5")) %>%
dplyr::left_join(seq_lookup, by = c("subject","Block","trial")) %>%
tidyr::pivot_longer(dplyr::starts_with("rms_"), names_to = "Axis", values_to = "RMS") %>%
dplyr::mutate(Axis = toupper(sub("^rms_", "", Axis)))#1.1 Training phase comparison preparation and execution
# === TRAINING (Blocks 1–3) — Combined figure: Preparation (top) + Execution (bottom)
# Boxplots + jitter, no outliers, single X/Y/Z headers (top only), custom x labels
# Long-format data with Difficulty labels
exec_tr_long <- exec_data %>%
dplyr::filter(Block %in% 1:3) %>%
tidyr::pivot_longer(dplyr::starts_with("rms_"),
names_to = "Axis", values_to = "RMS") %>%
dplyr::mutate(
Axis = toupper(sub("^rms_", "", Axis)),
Difficulty = factor(Block, levels = c(1, 2, 3),
labels = c("6 steps", "12 steps", "18 steps"))
)
prep_tr_long <- prep_rms %>%
dplyr::filter(Block %in% 1:3) %>%
tidyr::pivot_longer(dplyr::starts_with("rms_"),
names_to = "Axis", values_to = "RMS") %>%
dplyr::mutate(
Axis = toupper(sub("^rms_", "", Axis)),
Difficulty = factor(Block, levels = c(1, 2, 3),
labels = c("6 steps", "12 steps", "18 steps"))
)
# Preparation (top)
p_train_prep_box <- ggplot(prep_tr_long, aes(x = Difficulty, y = RMS, fill = Difficulty)) +
geom_boxplot(width = 0.65, outlier.shape = NA) +
geom_jitter(aes(color = Difficulty),
width = 0.20, height = 0, size = 0.7, alpha = 0.35, shape = 16, stroke = 0) +
facet_wrap(~ Axis, nrow = 1, strip.position = "top") +
coord_cartesian(ylim = c(0, 0.4)) +
labs(title = "Training Phase — Preparation",
x = "Difficulty", y = "RMS") +
theme_classic() +
theme(strip.text.x = element_text(face = "bold")) +
guides(fill = "none", color = "none")
# Execution (bottom)
p_train_exec_box <- ggplot(exec_tr_long, aes(x = Difficulty, y = RMS, fill = Difficulty)) +
geom_boxplot(width = 0.65, outlier.shape = NA) +
geom_jitter(aes(color = Difficulty),
width = 0.20, height = 0, size = 0.7, alpha = 0.35, shape = 16, stroke = 0) +
facet_wrap(~ Axis, nrow = 1, strip.position = "top") +
coord_cartesian(ylim = c(0, 2.5)) +
labs(title = "Training Phase — Execution ",
x = "Difficulty", y = "RMS") +
theme_classic() +
theme(strip.text.x = element_blank()) +
guides(fill = "none", color = "none")
# Combine vertically
p_train_prep_box / p_train_exec_box
#1.2 Test phase comparison preparation and execution
# === TEST BLOCKS (4–5)
# Preparation (top) + Execution (bottom), Condition = Familiar/Unfamiliar
library(dplyr)
library(tidyr)
library(ggplot2)
library(patchwork)
# Ensure Difficulty and Condition labels
prep_b45_plot <- prep_b45 %>%
mutate(
Difficulty = factor(SeqLen,
levels = c("6-step","12-step","18-step"),
labels = c("6 steps","12 steps","18 steps")),
Condition = factor(Block, levels = c("4","5"),
labels = c("Familiar","Unfamiliar"))
)
exec_b45_plot <- exec_b45 %>%
mutate(
Difficulty = factor(SeqLen,
levels = c("6-step","12-step","18-step"),
labels = c("6 steps","12 steps","18 steps")),
Condition = factor(Block, levels = c("4","5"),
labels = c("Familiar","Unfamiliar"))
)
dodge_w <- 0.65
jit_w <- 0.15
# --- Preparation (top) ---
p_test_prep_combined <- ggplot(prep_b45_plot, aes(x = Difficulty, y = RMS, fill = Condition)) +
geom_boxplot(outlier.shape = NA, width = 0.6,
position = position_dodge(width = dodge_w)) +
geom_point(aes(color = Condition),
position = position_jitterdodge(jitter.width = jit_w, dodge.width = dodge_w),
size = 0.6, alpha = 0.30, shape = 16, stroke = 0) +
facet_wrap(~ Axis, nrow = 1, strip.position = "top") +
coord_cartesian(ylim = c(0, 0.4)) +
labs(title = "Preparation - Test Blocks (4–5)",
x = "Difficulty", y = "RMS") +
theme_classic() +
theme(strip.text.x = element_text(face = "bold")) +
scale_fill_manual(name = "Condition",
values = c(Familiar = "#F8766D", Unfamiliar = "#00BFC4")) +
scale_color_manual(values = c(Familiar = "#F8766D", Unfamiliar = "#00BFC4"),
guide = "none") # show only one legend (fill)
# --- Execution (bottom) ---
p_test_exec_combined <- ggplot(exec_b45_plot, aes(x = Difficulty, y = RMS, fill = Condition)) +
geom_boxplot(outlier.shape = NA, width = 0.6,
position = position_dodge(width = dodge_w)) +
geom_point(aes(color = Condition),
position = position_jitterdodge(jitter.width = jit_w, dodge.width = dodge_w),
size = 0.6, alpha = 0.30, shape = 16, stroke = 0) +
facet_wrap(~ Axis, nrow = 1, strip.position = "top") +
coord_cartesian(ylim = c(0, 2.5)) +
labs(title = "Execution",
x = "Difficulty", y = "RMS") +
theme_classic() +
theme(strip.text.x = element_blank()) + # X/Y/Z only on top row
scale_fill_manual(name = "Condition",
values = c(Familiar = "#F8766D", Unfamiliar = "#00BFC4")) +
scale_color_manual(values = c(Familiar = "#F8766D", Unfamiliar = "#00BFC4"),
guide = "none") # keep one legend
# Combine vertically and show the legend at the bottom
(p_test_prep_combined / p_test_exec_combined) +
plot_layout(guides = "collect") & theme(legend.position = "bottom")
# ==== #1.3 Complement: Pairwise Block comparisons matching the plots ====
# - TRAINING (Blocks 1–3): within-phase (Prep/Exec), per axis — Tukey among 1,2,3
# - TEST (Blocks 4–5): within-phase AND within SeqLen (6/12/18), per axis — Block 4 vs 5
# Model used in each subset: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
suppressPackageStartupMessages({
library(dplyr)
library(lme4)
library(emmeans)
})
emm_options(lmer.df = "asymptotic")
# -------- TRAINING: Blocks 1–3 (within-phase) --------
pairwise_training_blocks <- function(rms_combined) {
for (axis in c("x","y","z")) {
axis_col <- paste0("rms_", axis)
# long-ish subset per phase
for (ph in c("Preparation","Execution")) {
d <- rms_combined %>%
filter(phase == ph, Block %in% c("1","2","3")) %>%
transmute(
subject, Trial, phase,
Block = factor(Block, levels = c("1","2","3")),
Accuracy,
RMS = .data[[axis_col]]
) %>%
droplevels()
if (nrow(d) == 0) next
cat("\n\n====================\n",
"TRAINING | Axis ", toupper(axis), " | Phase: ", ph,
"\n====================\n", sep = "")
m <- lmer(RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial), data = d, REML = TRUE)
em_blk <- emmeans(m, ~ Block) # EMMs for Blocks 1–3 within this phase
cat("\nEstimated Marginal Means (Blocks 1–3):\n")
print(summary(em_blk))
cat("\nPairwise (Tukey) among Blocks 1–3:\n")
print(pairs(em_blk, adjust = "tukey"))
rm(m, em_blk); invisible(gc())
}
}
}
# -------- TEST: Blocks 4–5 (within-phase AND within SeqLen) --------
pairwise_test_blocks_by_length <- function(rms_combined) {
if (!exists("sw_all")) {
stop("Test-phase length-specific comparisons require `sw_all` (from step-wise prep) to be available.")
}
# Build sequence-length lookup from sw_all (actual detected step_count per trial)
seq_lookup <- sw_all %>%
distinct(subject, Block, trial, step_count) %>%
filter(Block %in% c(4,5)) %>%
mutate(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial),
SeqLen = factor(paste0(step_count, " steps"),
levels = c("6 steps","12 steps","18 steps"))
) %>%
select(subject, Block_chr, trial_chr, SeqLen)
# Attach SeqLen to phase-level RMS for blocks 4–5
rb45 <- rms_combined %>%
filter(Block %in% c("4","5")) %>%
mutate(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial)
) %>%
left_join(seq_lookup, by = c("subject","Block_chr","trial_chr")) %>%
mutate(
Block = factor(Block, levels = c("4","5")),
SeqLen = droplevels(SeqLen)
)
for (axis in c("x","y","z")) {
axis_col <- paste0("rms_", axis)
for (ph in c("Preparation","Execution")) {
for (sl in c("6 steps","12 steps","18 steps")) {
dd <- rb45 %>%
filter(phase == ph, SeqLen == sl) %>%
transmute(
subject, Trial, phase, SeqLen,
Block, Accuracy,
RMS = .data[[axis_col]]
) %>%
droplevels()
if (nrow(dd) == 0 || nlevels(dd$Block) < 2) next
cat("\n\n--------------------\n",
"TEST | Axis ", toupper(axis), " | Phase: ", ph, " | SeqLen: ", sl,
"\n--------------------\n", sep = "")
m <- lmer(RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial), data = dd, REML = TRUE)
em_blk <- emmeans(m, ~ Block) # Block 4 vs 5 within this phase × SeqLen
cat("\nEstimated Marginal Means (Block 4 vs 5):\n")
print(summary(em_blk))
cat("\nPairwise (Tukey) Block 4 vs 5:\n")
print(pairs(em_blk, adjust = "tukey"))
rm(m, em_blk); invisible(gc())
}
}
}
}
# ---- Run both analyses ----
pairwise_training_blocks(rms_combined)
====================
TRAINING | Axis X | Phase: Preparation
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.0599 0.0141 Inf 0.0323 0.0875
2 0.1208 0.0138 Inf 0.0938 0.1479
3 0.1686 0.0139 Inf 0.1414 0.1958
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.0609 0.00876 Inf -6.953 <.0001
Block1 - Block3 -0.1087 0.00897 Inf -12.120 <.0001
Block2 - Block3 -0.0477 0.00846 Inf -5.645 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis X | Phase: Execution
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.796 0.0657 Inf 0.667 0.925
2 0.713 0.0656 Inf 0.584 0.842
3 0.596 0.0656 Inf 0.467 0.724
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0829 0.0107 Inf 7.784 <.0001
Block1 - Block3 0.2004 0.0109 Inf 18.394 <.0001
Block2 - Block3 0.1175 0.0101 Inf 11.589 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Y | Phase: Preparation
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.0587 0.0150 Inf 0.0294 0.088
2 0.1290 0.0147 Inf 0.1003 0.158
3 0.1807 0.0147 Inf 0.1518 0.210
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.0703 0.00993 Inf -7.084 <.0001
Block1 - Block3 -0.1220 0.01020 Inf -12.008 <.0001
Block2 - Block3 -0.0516 0.00958 Inf -5.388 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Y | Phase: Execution
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.846 0.0755 Inf 0.698 0.994
2 0.758 0.0754 Inf 0.610 0.906
3 0.624 0.0754 Inf 0.476 0.772
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0881 0.0124 Inf 7.120 <.0001
Block1 - Block3 0.2222 0.0126 Inf 17.567 <.0001
Block2 - Block3 0.1341 0.0118 Inf 11.391 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Z | Phase: Preparation
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.0534 0.0257 Inf 0.00307 0.104
2 0.1728 0.0252 Inf 0.12348 0.222
3 0.2521 0.0253 Inf 0.20262 0.302
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.1194 0.0164 Inf -7.291 <.0001
Block1 - Block3 -0.1988 0.0168 Inf -11.864 <.0001
Block2 - Block3 -0.0794 0.0158 Inf -5.022 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Z | Phase: Execution
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 1.30 0.124 Inf 1.061 1.55
2 1.23 0.124 Inf 0.986 1.47
3 1.05 0.124 Inf 0.813 1.30
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0751 0.0210 Inf 3.583 0.0010
Block1 - Block3 0.2486 0.0214 Inf 11.615 <.0001
Block2 - Block3 0.1735 0.0199 Inf 8.710 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates pairwise_test_blocks_by_length(rms_combined)# ==== #1.3 Complement : Pairwise Block comparisons matching the plots ====
# - TRAINING (Blocks 1–3): within-phase (Prep/Exec), per axis — Tukey among 1,2,3
# - TEST (Blocks 4–5): within-phase AND within SeqLen (6/12/18), per axis — Block 4 vs 5
# Model in each subset: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
suppressPackageStartupMessages({
library(dplyr)
library(lme4)
library(lmerTest) # for Satterthwaite tests in summary() and anova()
library(emmeans)
library(car) # for Type II / III Wald χ²
})
emm_options(lmer.df = "asymptotic")
# -------- TRAINING: Blocks 1–3 (within-phase) --------
pairwise_training_blocks <- function(rms_combined) {
for (axis in c("x","y","z")) {
axis_col <- paste0("rms_", axis)
for (ph in c("Preparation","Execution")) {
d <- rms_combined %>%
filter(phase == ph, Block %in% c("1","2","3")) %>%
transmute(
subject, Trial, phase,
Block = factor(Block, levels = c("1","2","3")),
Accuracy,
RMS = .data[[axis_col]]
) %>%
droplevels()
if (nrow(d) == 0) next
cat("\n\n====================\n",
"TRAINING | Axis ", toupper(axis), " | Phase: ", ph,
"\n====================\n", sep = "")
m <- lmer(RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial), data = d, REML = TRUE)
cat("\n--- Model Summary (lmerTest; Satterthwaite t-tests) ---\n")
print(summary(m))
cat("\n--- lmerTest ANOVA (F-tests; Satterthwaite) ---\n")
print(anova(m)) # Type I in order of terms; informative with full summary above
cat("\n--- Type II Wald χ² (car::Anova) ---\n")
print(car::Anova(m, type = 2, test.statistic = "Chisq"))
cat("\n--- Type III Wald χ² (car::Anova; sum contrasts) ---\n")
print(car::Anova(m, type = 3, test.statistic = "Chisq"))
em_blk <- emmeans(m, ~ Block)
cat("\n--- Estimated Marginal Means (Blocks 1–3) ---\n")
print(summary(em_blk))
cat("\n--- Pairwise (Tukey) among Blocks 1–3 ---\n")
print(pairs(em_blk, adjust = "tukey"))
rm(m, em_blk); invisible(gc())
}
}
}
# -------- TEST: Blocks 4–5 (within-phase AND within SeqLen) --------
pairwise_test_blocks_by_length <- function(rms_combined) {
if (!exists("sw_all")) {
stop("Test-phase length-specific comparisons require `sw_all` (from step-wise prep) to be available.")
}
# Sequence-length lookup (actual detected per trial)
seq_lookup <- sw_all %>%
distinct(subject, Block, trial, step_count) %>%
filter(Block %in% c(4,5)) %>%
mutate(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial),
SeqLen = factor(paste0(step_count, " steps"),
levels = c("6 steps","12 steps","18 steps"))
) %>%
select(subject, Block_chr, trial_chr, SeqLen)
# Attach SeqLen to phase-level RMS for Blocks 4–5
rb45 <- rms_combined %>%
filter(Block %in% c("4","5")) %>%
mutate(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial)
) %>%
left_join(seq_lookup, by = c("subject","Block_chr","trial_chr")) %>%
mutate(
Block = factor(Block, levels = c("4","5")),
SeqLen = droplevels(SeqLen)
)
for (axis in c("x","y","z")) {
axis_col <- paste0("rms_", axis)
for (ph in c("Preparation","Execution")) {
for (sl in c("6 steps","12 steps","18 steps")) {
dd <- rb45 %>%
filter(phase == ph, SeqLen == sl) %>%
transmute(
subject, Trial, phase, SeqLen,
Block, Accuracy,
RMS = .data[[axis_col]]
) %>%
droplevels()
if (nrow(dd) == 0 || nlevels(dd$Block) < 2) next
cat("\n\n--------------------\n",
"TEST | Axis ", toupper(axis), " | Phase: ", ph, " | SeqLen: ", sl,
"\n--------------------\n", sep = "")
m <- lmer(RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial), data = dd, REML = TRUE)
cat("\n--- Model Summary (lmerTest; Satterthwaite t-tests) ---\n")
print(summary(m))
cat("\n--- lmerTest ANOVA (F-tests; Satterthwaite) ---\n")
print(anova(m))
cat("\n--- Type II Wald χ² (car::Anova) ---\n")
print(car::Anova(m, type = 2, test.statistic = "Chisq"))
cat("\n--- Type III Wald χ² (car::Anova; sum contrasts) ---\n")
print(car::Anova(m, type = 3, test.statistic = "Chisq"))
em_blk <- emmeans(m, ~ Block) # Block 4 vs 5 within this phase × SeqLen
cat("\n--- Estimated Marginal Means (Block 4 vs 5) ---\n")
print(summary(em_blk))
cat("\n--- Pairwise (Tukey) Block 4 vs 5 ---\n")
print(pairs(em_blk, adjust = "tukey"))
rm(m, em_blk); invisible(gc())
}
}
}
}
# ---- Run both analyses ----
pairwise_training_blocks(rms_combined)
====================
TRAINING | Axis X | Phase: Preparation
====================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
Data: d
REML criterion at convergence: -1053.8
Scaled residuals:
Min 1Q Median 3Q Max
-1.8161 -0.4221 -0.1614 0.1469 11.7183
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.0055881 0.07475
subject (Intercept) 0.0006911 0.02629
Residual 0.0407934 0.20197
Number of obs: 3378, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 1.164e-01 1.297e-02 5.473e+01 8.980 2.38e-12 ***
Block1 -5.654e-02 5.195e-03 3.325e+03 -10.883 < 2e-16 ***
Block2 4.397e-03 4.902e-03 3.321e+03 0.897 0.3698
Accuracy1 -7.152e-03 3.781e-03 3.217e+03 -1.892 0.0586 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2
Block1 0.021
Block2 -0.013 -0.506
Accuracy1 0.040 0.222 -0.041
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Block 5.9995 2.9998 2 3327.5 73.535 < 2e-16 ***
Accuracy 0.1460 0.1460 1 3216.5 3.579 0.05861 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Block 147.071 2 < 2e-16 ***
Accuracy 3.579 1 0.05852 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 80.633 1 < 2e-16 ***
Block 147.071 2 < 2e-16 ***
Accuracy 3.579 1 0.05852 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Estimated Marginal Means (Blocks 1–3) ---
Block emmean SE df asymp.LCL asymp.UCL
1 0.0599 0.0141 Inf 0.0323 0.0875
2 0.1208 0.0138 Inf 0.0938 0.1479
3 0.1686 0.0139 Inf 0.1414 0.1958
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) among Blocks 1–3 ---
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.0609 0.00876 Inf -6.953 <.0001
Block1 - Block3 -0.1087 0.00897 Inf -12.120 <.0001
Block2 - Block3 -0.0477 0.00846 Inf -5.645 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis X | Phase: Execution
====================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
Data: d
REML criterion at convergence: 120.9
Scaled residuals:
Min 1Q Median 3Q Max
-4.8704 -0.4840 -0.0071 0.4510 5.0806
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.003956 0.06289
subject (Intercept) 0.075076 0.27400
Residual 0.057055 0.23886
Number of obs: 3241, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 7.015e-01 6.537e-02 1.769e+01 10.732 3.58e-09 ***
Block1 9.445e-02 6.339e-03 3.183e+03 14.899 < 2e-16 ***
Block2 1.152e-02 5.905e-03 3.176e+03 1.951 0.0512 .
Accuracy1 -4.414e-02 4.608e-03 3.213e+03 -9.579 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2
Block1 0.007
Block2 -0.004 -0.514
Accuracy1 0.011 0.222 -0.042
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Block 19.8101 9.9050 2 3188.5 173.604 < 2.2e-16 ***
Accuracy 5.2351 5.2351 1 3213.2 91.755 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Block 347.208 2 < 2.2e-16 ***
Accuracy 91.755 1 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 115.167 1 < 2.2e-16 ***
Block 347.208 2 < 2.2e-16 ***
Accuracy 91.755 1 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Estimated Marginal Means (Blocks 1–3) ---
Block emmean SE df asymp.LCL asymp.UCL
1 0.796 0.0657 Inf 0.667 0.925
2 0.713 0.0656 Inf 0.584 0.842
3 0.596 0.0656 Inf 0.467 0.724
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) among Blocks 1–3 ---
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0829 0.0107 Inf 7.784 <.0001
Block1 - Block3 0.2004 0.0109 Inf 18.394 <.0001
Block2 - Block3 0.1175 0.0101 Inf 11.589 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Y | Phase: Preparation
====================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
Data: d
REML criterion at convergence: -218.7
Scaled residuals:
Min 1Q Median 3Q Max
-1.5091 -0.4013 -0.1592 0.1394 24.5361
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.0062547 0.07909
subject (Intercept) 0.0006933 0.02633
Residual 0.0523860 0.22888
Number of obs: 3378, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 1.228e-01 1.363e-02 5.382e+01 9.007 2.5e-12 ***
Block1 -6.411e-02 5.886e-03 3.328e+03 -10.892 < 2e-16 ***
Block2 6.241e-03 5.554e-03 3.323e+03 1.124 0.2612
Accuracy1 -7.212e-03 4.274e-03 3.147e+03 -1.687 0.0917 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2
Block1 0.023
Block2 -0.014 -0.507
Accuracy1 0.043 0.222 -0.041
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Block 7.5748 3.7874 2 3329.9 72.2978 < 2e-16 ***
Accuracy 0.1491 0.1491 1 3146.7 2.8468 0.09165 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Block 144.5956 2 < 2e-16 ***
Accuracy 2.8468 1 0.09156 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 81.1175 1 < 2e-16 ***
Block 144.5956 2 < 2e-16 ***
Accuracy 2.8468 1 0.09156 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Estimated Marginal Means (Blocks 1–3) ---
Block emmean SE df asymp.LCL asymp.UCL
1 0.0587 0.0150 Inf 0.0294 0.088
2 0.1290 0.0147 Inf 0.1003 0.158
3 0.1807 0.0147 Inf 0.1518 0.210
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) among Blocks 1–3 ---
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.0703 0.00993 Inf -7.084 <.0001
Block1 - Block3 -0.1220 0.01020 Inf -12.008 <.0001
Block2 - Block3 -0.0516 0.00958 Inf -5.388 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Y | Phase: Execution
====================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
Data: d
REML criterion at convergence: 1078.6
Scaled residuals:
Min 1Q Median 3Q Max
-4.6672 -0.4816 0.0024 0.4511 6.6133
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.003739 0.06115
subject (Intercept) 0.099724 0.31579
Residual 0.077019 0.27752
Number of obs: 3241, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 7.429e-01 7.513e-02 1.750e+01 9.888 1.39e-08 ***
Block1 1.034e-01 7.362e-03 3.189e+03 14.050 < 2e-16 ***
Block2 1.532e-02 6.859e-03 3.181e+03 2.233 0.0256 *
Accuracy1 -4.498e-02 5.346e-03 3.219e+03 -8.413 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2
Block1 0.007
Block2 -0.004 -0.514
Accuracy1 0.011 0.222 -0.042
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Block 24.5699 12.2849 2 3195.2 159.505 < 2.2e-16 ***
Accuracy 5.4517 5.4517 1 3219.5 70.784 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Block 319.010 2 < 2.2e-16 ***
Accuracy 70.784 1 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 97.776 1 < 2.2e-16 ***
Block 319.010 2 < 2.2e-16 ***
Accuracy 70.784 1 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Estimated Marginal Means (Blocks 1–3) ---
Block emmean SE df asymp.LCL asymp.UCL
1 0.846 0.0755 Inf 0.698 0.994
2 0.758 0.0754 Inf 0.610 0.906
3 0.624 0.0754 Inf 0.476 0.772
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) among Blocks 1–3 ---
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0881 0.0124 Inf 7.120 <.0001
Block1 - Block3 0.2222 0.0126 Inf 17.567 <.0001
Block2 - Block3 0.1341 0.0118 Inf 11.391 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Z | Phase: Preparation
====================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
Data: d
REML criterion at convergence: 3162.3
Scaled residuals:
Min 1Q Median 3Q Max
-1.4689 -0.3958 -0.1519 0.1488 14.4245
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.017764 0.13328
subject (Intercept) 0.002477 0.04977
Residual 0.142476 0.37746
Number of obs: 3378, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 1.594e-01 2.354e-02 5.443e+01 6.772 9.34e-09 ***
Block1 -1.061e-01 9.708e-03 3.326e+03 -10.925 < 2e-16 ***
Block2 1.335e-02 9.161e-03 3.322e+03 1.458 0.1450
Accuracy1 -1.560e-02 7.065e-03 3.226e+03 -2.208 0.0273 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2
Block1 0.022
Block2 -0.013 -0.507
Accuracy1 0.042 0.222 -0.041
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Block 20.1906 10.0953 2 3328.6 70.8559 < 2e-16 ***
Accuracy 0.6949 0.6949 1 3225.8 4.8771 0.02729 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Block 141.7119 2 < 2e-16 ***
Accuracy 4.8771 1 0.02722 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 45.8537 1 1.274e-11 ***
Block 141.7119 2 < 2.2e-16 ***
Accuracy 4.8771 1 0.02722 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Estimated Marginal Means (Blocks 1–3) ---
Block emmean SE df asymp.LCL asymp.UCL
1 0.0534 0.0257 Inf 0.00307 0.104
2 0.1728 0.0252 Inf 0.12348 0.222
3 0.2521 0.0253 Inf 0.20262 0.302
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) among Blocks 1–3 ---
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.1194 0.0164 Inf -7.291 <.0001
Block1 - Block3 -0.1988 0.0168 Inf -11.864 <.0001
Block2 - Block3 -0.0794 0.0158 Inf -5.022 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Z | Phase: Execution
====================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial)
Data: d
REML criterion at convergence: 4479
Scaled residuals:
Min 1Q Median 3Q Max
-4.5636 -0.4699 -0.0113 0.4195 5.9733
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.008101 0.09001
subject (Intercept) 0.268090 0.51777
Residual 0.220928 0.47003
Number of obs: 3241, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 1.196e+00 1.230e-01 1.741e+01 9.717 1.89e-08 ***
Block1 1.079e-01 1.246e-02 3.191e+03 8.658 < 2e-16 ***
Block2 3.280e-02 1.161e-02 3.180e+03 2.824 0.00477 **
Accuracy1 -8.618e-02 9.043e-03 3.222e+03 -9.530 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) Block1 Block2
Block1 0.007
Block2 -0.004 -0.515
Accuracy1 0.011 0.222 -0.042
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Block 32.498 16.249 2 3197.0 73.549 < 2.2e-16 ***
Accuracy 20.065 20.065 1 3222.1 90.820 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Block 147.10 2 < 2.2e-16 ***
Accuracy 90.82 1 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 94.426 1 < 2.2e-16 ***
Block 147.098 2 < 2.2e-16 ***
Accuracy 90.820 1 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Estimated Marginal Means (Blocks 1–3) ---
Block emmean SE df asymp.LCL asymp.UCL
1 1.30 0.124 Inf 1.061 1.55
2 1.23 0.124 Inf 0.986 1.47
3 1.05 0.124 Inf 0.813 1.30
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) among Blocks 1–3 ---
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0751 0.0210 Inf 3.583 0.0010
Block1 - Block3 0.2486 0.0214 Inf 11.615 <.0001
Block2 - Block3 0.1735 0.0199 Inf 8.710 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates pairwise_test_blocks_by_length(rms_combined)#2.1 comparison of sequence lengths training phase
# ==== TRAINING (Blocks 1–3): pairwise Block comparisons within each phase, per axis ====
# Uses the same family as plots: RMS ~ Block + Accuracy + (1|subject) + (1|Trial)
suppressPackageStartupMessages({
library(dplyr)
library(lme4)
library(emmeans)
})
emm_options(lmer.df = "asymptotic")
pairwise_training_blocks <- function(rms_combined) {
for (axis in c("x","y","z")) {
axis_col <- paste0("rms_", axis)
for (ph in c("Preparation","Execution")) {
d <- rms_combined %>%
filter(phase == ph, Block %in% c("1","2","3")) %>%
transmute(
subject, Trial, phase,
Block = factor(Block, levels = c("1","2","3")),
Accuracy,
RMS = .data[[axis_col]]
) %>%
droplevels()
if (nrow(d) == 0 || nlevels(d$Block) < 2) next
cat("\n\n====================\n",
"TRAINING | Axis ", toupper(axis), " | Phase: ", ph,
"\n====================\n", sep = "")
m <- lmer(RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial), data = d, REML = TRUE)
em_blk <- emmeans(m, ~ Block)
cat("\nEstimated Marginal Means (Blocks 1–3):\n"); print(summary(em_blk))
cat("\nPairwise (Tukey) among Blocks 1–3:\n"); print(pairs(em_blk, adjust = "tukey"))
rm(m, em_blk); invisible(gc())
}
}
}
# Run training comparisons
pairwise_training_blocks(rms_combined)
====================
TRAINING | Axis X | Phase: Preparation
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.0599 0.0141 Inf 0.0323 0.0875
2 0.1208 0.0138 Inf 0.0938 0.1479
3 0.1686 0.0139 Inf 0.1414 0.1958
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.0609 0.00876 Inf -6.953 <.0001
Block1 - Block3 -0.1087 0.00897 Inf -12.120 <.0001
Block2 - Block3 -0.0477 0.00846 Inf -5.645 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis X | Phase: Execution
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.796 0.0657 Inf 0.667 0.925
2 0.713 0.0656 Inf 0.584 0.842
3 0.596 0.0656 Inf 0.467 0.724
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0829 0.0107 Inf 7.784 <.0001
Block1 - Block3 0.2004 0.0109 Inf 18.394 <.0001
Block2 - Block3 0.1175 0.0101 Inf 11.589 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Y | Phase: Preparation
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.0587 0.0150 Inf 0.0294 0.088
2 0.1290 0.0147 Inf 0.1003 0.158
3 0.1807 0.0147 Inf 0.1518 0.210
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.0703 0.00993 Inf -7.084 <.0001
Block1 - Block3 -0.1220 0.01020 Inf -12.008 <.0001
Block2 - Block3 -0.0516 0.00958 Inf -5.388 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Y | Phase: Execution
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.846 0.0755 Inf 0.698 0.994
2 0.758 0.0754 Inf 0.610 0.906
3 0.624 0.0754 Inf 0.476 0.772
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0881 0.0124 Inf 7.120 <.0001
Block1 - Block3 0.2222 0.0126 Inf 17.567 <.0001
Block2 - Block3 0.1341 0.0118 Inf 11.391 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Z | Phase: Preparation
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 0.0534 0.0257 Inf 0.00307 0.104
2 0.1728 0.0252 Inf 0.12348 0.222
3 0.2521 0.0253 Inf 0.20262 0.302
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 -0.1194 0.0164 Inf -7.291 <.0001
Block1 - Block3 -0.1988 0.0168 Inf -11.864 <.0001
Block2 - Block3 -0.0794 0.0158 Inf -5.022 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
====================
TRAINING | Axis Z | Phase: Execution
====================
Estimated Marginal Means (Blocks 1–3):
Block emmean SE df asymp.LCL asymp.UCL
1 1.30 0.124 Inf 1.061 1.55
2 1.23 0.124 Inf 0.986 1.47
3 1.05 0.124 Inf 0.813 1.30
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
Pairwise (Tukey) among Blocks 1–3:
contrast estimate SE df z.ratio p.value
Block1 - Block2 0.0751 0.0210 Inf 3.583 0.0010
Block1 - Block3 0.2486 0.0214 Inf 11.615 <.0001
Block2 - Block3 0.1735 0.0199 Inf 8.710 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates #2.1 comparison of sequence lengths test phase, and comparison of familiar vs unfamiliar
# ==== TEST (Blocks 4–5): block-vs-block within each length AND within-block among lengths ====
# Models:
# A) Block 4 vs 5 within phase & length: RMS ~ Block + Accuracy + (1|subject) + (1|Trial)
# B) Lengths (6/12/18) within block & phase: RMS ~ SeqLen + Accuracy + (1|subject) + (1|Trial)
suppressPackageStartupMessages({
library(dplyr)
library(lme4)
library(emmeans)
})
emm_options(lmer.df = "asymptotic")
pairwise_test_blocks_and_lengths <- function(rms_combined) {
if (!exists("sw_all")) {
stop("This analysis needs `sw_all` (step-wise table) to derive sequence lengths for Blocks 4–5.")
}
# Build a unique per-trial sequence length lookup (6/12/18 steps) from sw_all
seq_lookup <- sw_all %>%
group_by(subject, Block, trial) %>%
summarise(step_count = max(step_count, na.rm = TRUE), .groups = "drop") %>% # ensure unique per trial
filter(Block %in% c(4, 5)) %>%
transmute(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial),
SeqLen = factor(paste0(step_count, " steps"),
levels = c("6 steps","12 steps","18 steps"))
)
# Attach sequence length to the phase-level RMS rows for blocks 4–5
rb45 <- rms_combined %>%
filter(Block %in% c("4","5")) %>%
mutate(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial)
) %>%
left_join(seq_lookup, by = c("subject","Block_chr","trial_chr")) %>%
mutate(
Block = factor(Block, levels = c("4","5")),
SeqLen = droplevels(SeqLen)
)
# ---------- (A) Block 4 vs 5 within each length & phase ----------
for (axis in c("x","y","z")) {
axis_col <- paste0("rms_", axis)
for (ph in c("Preparation","Execution")) {
for (sl in c("6 steps","12 steps","18 steps")) {
dd <- rb45 %>%
filter(phase == ph, SeqLen == sl) %>%
transmute(
subject, Trial, phase, SeqLen,
Block, Accuracy,
RMS = .data[[axis_col]]
) %>% droplevels()
if (nrow(dd) == 0 || nlevels(dd$Block) < 2) next
cat("\n\n--------------------\n",
"TEST (Between blocks) | Axis ", toupper(axis),
" | Phase: ", ph, " | SeqLen: ", sl,
"\n--------------------\n", sep = "")
mA <- lmer(RMS ~ Block + Accuracy + (1 | subject) + (1 | Trial), data = dd, REML = TRUE)
em_blk <- emmeans(mA, ~ Block) # 4 vs 5
cat("\nEstimated Marginal Means (Block 4 vs 5):\n"); print(summary(em_blk))
cat("\nPairwise (Tukey) Block 4 vs 5:\n"); print(pairs(em_blk, adjust = "tukey"))
rm(mA, em_blk); invisible(gc())
}
}
}
# ---------- (B) Within each block: compare sequence lengths (6 vs 12 vs 18) per phase ----------
for (axis in c("x","y","z")) {
axis_col <- paste0("rms_", axis)
for (ph in c("Preparation","Execution")) {
for (blk in c("4","5")) {
dd <- rb45 %>%
filter(phase == ph, Block == blk) %>%
transmute(
subject, Trial, phase,
Block, SeqLen = factor(SeqLen, levels = c("6 steps","12 steps","18 steps")),
Accuracy,
RMS = .data[[axis_col]]
) %>% droplevels()
# Need at least 2 lengths present to compare
if (nrow(dd) == 0 || nlevels(dd$SeqLen) < 2) next
cat("\n\n====================\n",
"TEST (Within block) | Axis ", toupper(axis),
" | Phase: ", ph, " | Block: ", blk,
"\n====================\n", sep = "")
mB <- lmer(RMS ~ SeqLen + Accuracy + (1 | subject) + (1 | Trial), data = dd, REML = TRUE)
em_len <- emmeans(mB, ~ SeqLen)
cat("\nEstimated Marginal Means (SeqLen within Block ", blk, "):\n", sep = ""); print(summary(em_len))
cat("\nPairwise (Tukey) among 6/12/18 steps within Block ", blk, ":\n", sep = ""); print(pairs(em_len, adjust = "tukey"))
rm(mB, em_len); invisible(gc())
}
}
}
}
# Run test-phase comparisons
pairwise_test_blocks_and_lengths(rms_combined)# ==== #2.1c: Execution-phase % difference — Block 4 vs Block 5 (per axis & overall) ====
suppressPackageStartupMessages({
library(dplyr); library(tidyr); library(tibble)
library(lme4); library(lmerTest); library(emmeans)
})
emm_options(lmer.df = "asymptotic")
percent_table_exec_block4_vs5 <- function(rms_combined) {
if (!exists("sw_all")) {
stop("This analysis needs `sw_all` (step-wise table) to derive sequence lengths for Blocks 4–5).")
}
# Per-trial sequence length lookup (6/12/18)
seq_lookup <- sw_all %>%
group_by(subject, Block, trial) %>%
summarise(step_count = max(step_count, na.rm = TRUE), .groups = "drop") %>%
filter(Block %in% c(4, 5)) %>%
transmute(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial),
SeqLen = factor(
paste0(step_count, " steps"),
levels = c("6 steps","12 steps","18 steps")
)
)
# Execution-only rows for Blocks 4–5, joined with SeqLen
rb45_exec <- rms_combined %>%
filter(phase == "Execution", Block %in% c("4","5")) %>%
mutate(
subject = as.character(subject),
Block_chr = as.character(Block),
trial_chr = as.character(trial)
) %>%
left_join(seq_lookup, by = c("subject","Block_chr","trial_chr")) %>%
mutate(
Block = factor(Block, levels = c("4","5")),
SeqLen = droplevels(SeqLen),
Trial = factor(Trial)
)
# ----- Per-axis models (adjusted for SeqLen) -----
axis_rows <- lapply(c(x = "X", y = "Y", z = "Z"), function(ax_lab) {
col <- paste0("rms_", tolower(ax_lab))
dd <- rb45_exec %>%
transmute(subject, Trial, Block, Accuracy, SeqLen, RMS = .data[[col]]) %>%
tidyr::drop_na(subject, Trial, Block, Accuracy, SeqLen, RMS) %>%
droplevels()
if (nrow(dd) == 0 || nlevels(dd$Block) < 2) return(NULL)
m <- lmer(
RMS ~ Block + SeqLen + Accuracy + (1 | subject) + (1 | Trial),
data = dd, REML = TRUE
)
em <- summary(emmeans(m, ~ Block)) %>% as_tibble()
b4 <- em %>% filter(Block == "4") %>% pull(emmean)
b5 <- em %>% filter(Block == "5") %>% pull(emmean)
tibble(
Scope = "Per Axis",
Axis = ax_lab,
Block4_EMM = b4,
Block5_EMM = b5,
Diff_5_minus_4 = b5 - b4,
Percent_Faster_B4_vs_B5 = 100 * (b5 - b4) / b5
)
})
per_axis_tbl <- bind_rows(axis_rows)
# ----- Overall across axes (adjusted for Axis and SeqLen) -----
overall_dd <- rb45_exec %>%
select(subject, Trial, Block, Accuracy, SeqLen, rms_x, rms_y, rms_z) %>%
tidyr::drop_na(subject, Trial, Block, Accuracy, SeqLen, rms_x, rms_y, rms_z) %>%
pivot_longer(c(rms_x, rms_y, rms_z), names_to = "Axis", values_to = "RMS") %>%
mutate(
Axis = dplyr::recode(Axis, "rms_x" = "X", "rms_y" = "Y", "rms_z" = "Z"),
Axis = factor(Axis, levels = c("X","Y","Z"))
) %>%
drop_na(RMS) %>%
droplevels()
overall_row <- {
if (nrow(overall_dd) > 0 && nlevels(overall_dd$Block) > 1) {
m_all <- lmer(
RMS ~ Block + Axis + SeqLen + Accuracy + (1 | subject) + (1 | Trial),
data = overall_dd, REML = TRUE
)
em_all <- summary(emmeans(m_all, ~ Block)) %>% as_tibble()
b4 <- em_all %>% filter(Block == "4") %>% pull(emmean)
b5 <- em_all %>% filter(Block == "5") %>% pull(emmean)
tibble(
Scope = "Overall (All Axes)",
Axis = "All",
Block4_EMM = b4,
Block5_EMM = b5,
Diff_5_minus_4 = b5 - b4,
Percent_Faster_B4_vs_B5 = 100 * (b5 - b4) / b5
)
} else {
NULL
}
}
# If both parts are empty, return a well-formed empty table (prevents mutate errors)
if ((is.null(per_axis_tbl) || nrow(per_axis_tbl) == 0) && is.null(overall_row)) {
message("No valid data for Block 4 vs 5 percentage table after filtering; returning empty table.")
return(tibble(
Scope = character(),
Axis = character(),
Block4_EMM = double(),
Block5_EMM = double(),
Diff_5_minus_4 = double(),
Percent_Faster_B4_vs_B5 = double()
))
}
out_tbl <- bind_rows(
per_axis_tbl,
if (is.null(overall_row)) tibble(
Scope = character(), Axis = character(),
Block4_EMM = double(), Block5_EMM = double(),
Diff_5_minus_4 = double(), Percent_Faster_B4_vs_B5 = double()
) else overall_row
)
if (nrow(out_tbl) == 0) {
message("No rows in Block 4 vs 5 percentage table; returning empty table.")
return(out_tbl)
}
out_tbl <- out_tbl %>%
mutate(
Block4_EMM = round(Block4_EMM, 3),
Block5_EMM = round(Block5_EMM, 3),
Diff_5_minus_4 = round(Diff_5_minus_4, 3),
Percent_Faster_B4_vs_B5 = round(Percent_Faster_B4_vs_B5, 1)
) %>%
arrange(match(Scope, c("Per Axis","Overall (All Axes)")), Axis)
cat("\n\n==============================================\n")
cat("Execution phase — % faster of Block 4 vs Block 5\n")
cat("Percent = 100 * (Block5_EMM - Block4_EMM) / Block5_EMM\n")
cat("EMMs are adjusted for SeqLen (per-axis) and for Axis + SeqLen (overall).\n")
cat("==============================================\n")
print(out_tbl)
invisible(out_tbl)
}
# ---- Run it ----
percent_table_exec_block4_vs5(rms_combined)No valid data for Block 4 vs 5 percentage table after filtering; returning empty table.# A tibble: 0 × 6
# ℹ 6 variables: Scope <chr>, Axis <chr>, Block4_EMM <dbl>, Block5_EMM <dbl>,
# Diff_5_minus_4 <dbl>, Percent_Faster_B4_vs_B5 <dbl>#3.1 Concatenation analysis
# --- Build step-wise datasets for training (Blocks 1–3) and test (Blocks 4–5) ---
# Uses your earlier helper:
# compute_stepwise_rms(tagged_exec_df, max_steps_keep = 18)
# -> one row per detected step per trial: subject, Block, trial, Step, RMS (x/y/z), Axis ("x","y","z"), step_count
# And accuracy join helper:
# add_accuracy_to(df_core, df_lookup = all_data_mixed)
# 1) Compute all step-wise rows (up to 18) from tagged_data
stepwise_all <- compute_stepwise_rms(tagged_data, max_steps_keep = 18) %>%
# Add trial-level Accuracy
add_accuracy_to(., all_data_mixed) %>%
# Ensure IDs/Axis are present in the expected format
dplyr::mutate(
trial_id = if ("trial_id" %in% names(.)) trial_id else interaction(subject, Block, trial, drop = TRUE),
Axis = factor(as.character(Axis), levels = c("x","y","z"))
)Warning in left_join(., acc_tbl, by = c("subject", "Block", "trial")): Detected an unexpected many-to-many relationship between `x` and `y`.
ℹ Row 1 of `x` matches multiple rows in `y`.
ℹ Row 3021 of `y` matches multiple rows in `x`.
ℹ If a many-to-many relationship is expected, set `relationship =
"many-to-many"` to silence this warning.# 2) TRAINING subsets used by .report_step_block(...)
# Block 1 -> 6 steps nominally
stepwise_6 <- stepwise_all %>% dplyr::filter(Block == 1)
# Block 2 -> 12 steps nominally
stepwise_12 <- stepwise_all %>% dplyr::filter(Block == 2)
# Block 3 -> 18 steps nominally
stepwise_18 <- stepwise_all %>% dplyr::filter(Block == 3)
# 3) TEST subsets by actual per-trial step_count (Blocks 4–5, mixed sequence lengths)
# Block 4
sw_b4_6 <- stepwise_all %>% dplyr::filter(Block == 4, step_count == 6)
sw_b4_12 <- stepwise_all %>% dplyr::filter(Block == 4, step_count == 12)
sw_b4_18 <- stepwise_all %>% dplyr::filter(Block == 4, step_count == 18)
# Block 5
sw_b5_6 <- stepwise_all %>% dplyr::filter(Block == 5, step_count == 6)
sw_b5_12 <- stepwise_all %>% dplyr::filter(Block == 5, step_count == 12)
sw_b5_18 <- stepwise_all %>% dplyr::filter(Block == 5, step_count == 18)# ==== TRAINING (Blocks 1–3): stepwise LMM + χ² + EMMs + all-pairs + adjacent (per block × axis) ====
suppressPackageStartupMessages({
library(dplyr); library(lme4); library(lmerTest); library(emmeans); library(car)
})
emm_options(lmer.df = "asymptotic")
.report_step_block <- function(df_block, block_label) {
for (ax in c("x","y","z")) {
dd <- df_block %>% filter(Axis == ax)
if (nrow(dd) == 0) next
dd <- dd %>%
mutate(
StepF = factor(Step, levels = sort(unique(Step))),
subject = factor(subject),
trial_id = factor(trial_id),
Accuracy = droplevels(Accuracy)
)
cat("\n\n==============================\n",
"TRAINING | Block ", block_label, " | Axis ", toupper(ax),
"\n==============================\n", sep = "")
m <- suppressWarnings(lmer(RMS ~ StepF + Accuracy + (1|subject) + (1|trial_id),
data = dd, REML = TRUE))
cat("\nType II Wald χ² (StepF & Accuracy):\n")
print(car::Anova(m, type = 2, test.statistic = "Chisq"))
if (nlevels(dd$Accuracy) >= 2) {
# EMMs by Accuracy
em <- emmeans(m, ~ StepF | Accuracy)
cat("\nEMMs per step | Accuracy:\n"); print(summary(em))
cat("\nAll-pairs (Tukey) among steps | Accuracy:\n")
print(pairs(em, adjust = "tukey"))
cat("\nAdjacent steps (consec; Holm) | Accuracy:\n")
print(contrast(em, method = "consec", by = "Accuracy", adjust = "holm"))
} else {
# Collapsed over Accuracy
em <- emmeans(m, ~ StepF)
cat("\nEMMs per step:\n"); print(summary(em))
cat("\nAll-pairs (Tukey) among steps:\n")
print(pairs(em, adjust = "tukey"))
cat("\nAdjacent steps (consec; Holm):\n")
print(contrast(em, method = "consec", adjust = "holm"))
}
rm(m, em); invisible(gc())
}
}
# Run training (Blocks 1,2,3)
.report_step_block(stepwise_6, "1 (6 steps)")
==============================
TRAINING | Block 1 (6 steps) | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 250.9866 5 < 2.2e-16 ***
Accuracy 8.0839 1 0.004466 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.670 0.113 Inf 0.449 0.891
2 0.866 0.113 Inf 0.645 1.087
3 0.984 0.113 Inf 0.762 1.205
4 0.877 0.113 Inf 0.656 1.099
5 0.860 0.113 Inf 0.639 1.082
6 0.719 0.113 Inf 0.497 0.940
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.719 0.112 Inf 0.499 0.939
2 0.915 0.112 Inf 0.695 1.135
3 1.033 0.112 Inf 0.813 1.253
4 0.926 0.112 Inf 0.706 1.146
5 0.909 0.112 Inf 0.689 1.129
6 0.768 0.112 Inf 0.548 0.988
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.19596 0.0229 Inf -8.558 <.0001
StepF1 - StepF3 -0.31377 0.0229 Inf -13.703 <.0001
StepF1 - StepF4 -0.20733 0.0229 Inf -9.055 <.0001
StepF1 - StepF5 -0.19010 0.0229 Inf -8.290 <.0001
StepF1 - StepF6 -0.04867 0.0230 Inf -2.113 0.2803
StepF2 - StepF3 -0.11781 0.0229 Inf -5.145 <.0001
StepF2 - StepF4 -0.01137 0.0229 Inf -0.497 0.9963
StepF2 - StepF5 0.00586 0.0229 Inf 0.256 0.9999
StepF2 - StepF6 0.14729 0.0230 Inf 6.396 <.0001
StepF3 - StepF4 0.10644 0.0229 Inf 4.649 <.0001
StepF3 - StepF5 0.12367 0.0229 Inf 5.393 <.0001
StepF3 - StepF6 0.26511 0.0230 Inf 11.511 <.0001
StepF4 - StepF5 0.01723 0.0229 Inf 0.752 0.9753
StepF4 - StepF6 0.15867 0.0230 Inf 6.889 <.0001
StepF5 - StepF6 0.14143 0.0231 Inf 6.134 <.0001
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.19596 0.0229 Inf -8.558 <.0001
StepF1 - StepF3 -0.31377 0.0229 Inf -13.703 <.0001
StepF1 - StepF4 -0.20733 0.0229 Inf -9.055 <.0001
StepF1 - StepF5 -0.19010 0.0229 Inf -8.290 <.0001
StepF1 - StepF6 -0.04867 0.0230 Inf -2.113 0.2803
StepF2 - StepF3 -0.11781 0.0229 Inf -5.145 <.0001
StepF2 - StepF4 -0.01137 0.0229 Inf -0.497 0.9963
StepF2 - StepF5 0.00586 0.0229 Inf 0.256 0.9999
StepF2 - StepF6 0.14729 0.0230 Inf 6.396 <.0001
StepF3 - StepF4 0.10644 0.0229 Inf 4.649 <.0001
StepF3 - StepF5 0.12367 0.0229 Inf 5.393 <.0001
StepF3 - StepF6 0.26511 0.0230 Inf 11.511 <.0001
StepF4 - StepF5 0.01723 0.0229 Inf 0.752 0.9753
StepF4 - StepF6 0.15867 0.0230 Inf 6.889 <.0001
StepF5 - StepF6 0.14143 0.0231 Inf 6.134 <.0001
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.1960 0.0229 Inf 8.558 <.0001
StepF3 - StepF2 0.1178 0.0229 Inf 5.145 <.0001
StepF4 - StepF3 -0.1064 0.0229 Inf -4.649 <.0001
StepF5 - StepF4 -0.0172 0.0229 Inf -0.752 0.4523
StepF6 - StepF5 -0.1414 0.0231 Inf -6.134 <.0001
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.1960 0.0229 Inf 8.558 <.0001
StepF3 - StepF2 0.1178 0.0229 Inf 5.145 <.0001
StepF4 - StepF3 -0.1064 0.0229 Inf -4.649 <.0001
StepF5 - StepF4 -0.0172 0.0229 Inf -0.752 0.4523
StepF6 - StepF5 -0.1414 0.0231 Inf -6.134 <.0001
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests
==============================
TRAINING | Block 1 (6 steps) | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 99.9658 5 < 2.2e-16 ***
Accuracy 7.5932 1 0.005859 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.796 0.135 Inf 0.530 1.06
2 0.887 0.135 Inf 0.621 1.15
3 1.002 0.135 Inf 0.736 1.27
4 0.893 0.135 Inf 0.628 1.16
5 0.815 0.135 Inf 0.550 1.08
6 0.826 0.136 Inf 0.560 1.09
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.847 0.135 Inf 0.582 1.11
2 0.938 0.135 Inf 0.674 1.20
3 1.053 0.135 Inf 0.789 1.32
4 0.944 0.135 Inf 0.680 1.21
5 0.866 0.135 Inf 0.602 1.13
6 0.877 0.135 Inf 0.612 1.14
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.09114 0.0239 Inf -3.810 0.0019
StepF1 - StepF3 -0.20603 0.0239 Inf -8.613 <.0001
StepF1 - StepF4 -0.09766 0.0239 Inf -4.082 0.0006
StepF1 - StepF5 -0.01955 0.0240 Inf -0.816 0.9647
StepF1 - StepF6 -0.02995 0.0241 Inf -1.245 0.8147
StepF2 - StepF3 -0.11489 0.0239 Inf -4.803 <.0001
StepF2 - StepF4 -0.00651 0.0239 Inf -0.272 0.9998
StepF2 - StepF5 0.07159 0.0240 Inf 2.988 0.0334
StepF2 - StepF6 0.06119 0.0241 Inf 2.543 0.1118
StepF3 - StepF4 0.10838 0.0239 Inf 4.531 0.0001
StepF3 - StepF5 0.18648 0.0240 Inf 7.784 <.0001
StepF3 - StepF6 0.17608 0.0241 Inf 7.318 <.0001
StepF4 - StepF5 0.07810 0.0240 Inf 3.260 0.0142
StepF4 - StepF6 0.06770 0.0241 Inf 2.814 0.0553
StepF5 - StepF6 -0.01040 0.0241 Inf -0.432 0.9981
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.09114 0.0239 Inf -3.810 0.0019
StepF1 - StepF3 -0.20603 0.0239 Inf -8.613 <.0001
StepF1 - StepF4 -0.09766 0.0239 Inf -4.082 0.0006
StepF1 - StepF5 -0.01955 0.0240 Inf -0.816 0.9647
StepF1 - StepF6 -0.02995 0.0241 Inf -1.245 0.8147
StepF2 - StepF3 -0.11489 0.0239 Inf -4.803 <.0001
StepF2 - StepF4 -0.00651 0.0239 Inf -0.272 0.9998
StepF2 - StepF5 0.07159 0.0240 Inf 2.988 0.0334
StepF2 - StepF6 0.06119 0.0241 Inf 2.543 0.1118
StepF3 - StepF4 0.10838 0.0239 Inf 4.531 0.0001
StepF3 - StepF5 0.18648 0.0240 Inf 7.784 <.0001
StepF3 - StepF6 0.17608 0.0241 Inf 7.318 <.0001
StepF4 - StepF5 0.07810 0.0240 Inf 3.260 0.0142
StepF4 - StepF6 0.06770 0.0241 Inf 2.814 0.0553
StepF5 - StepF6 -0.01040 0.0241 Inf -0.432 0.9981
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.0911 0.0239 Inf 3.810 0.0004
StepF3 - StepF2 0.1149 0.0239 Inf 4.803 <.0001
StepF4 - StepF3 -0.1084 0.0239 Inf -4.531 <.0001
StepF5 - StepF4 -0.0781 0.0240 Inf -3.260 0.0022
StepF6 - StepF5 0.0104 0.0241 Inf 0.432 0.6660
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.0911 0.0239 Inf 3.810 0.0004
StepF3 - StepF2 0.1149 0.0239 Inf 4.803 <.0001
StepF4 - StepF3 -0.1084 0.0239 Inf -4.531 <.0001
StepF5 - StepF4 -0.0781 0.0240 Inf -3.260 0.0022
StepF6 - StepF5 0.0104 0.0241 Inf 0.432 0.6660
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests
==============================
TRAINING | Block 1 (6 steps) | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 163.3760 5 <2e-16 ***
Accuracy 2.2879 1 0.1304
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.50 0.210 Inf 1.09 1.91
2 1.79 0.210 Inf 1.38 2.20
3 1.92 0.210 Inf 1.50 2.33
4 1.81 0.210 Inf 1.40 2.22
5 1.82 0.210 Inf 1.41 2.23
6 1.52 0.210 Inf 1.11 1.93
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.55 0.208 Inf 1.14 1.96
2 1.84 0.208 Inf 1.43 2.25
3 1.97 0.208 Inf 1.56 2.37
4 1.86 0.208 Inf 1.45 2.27
5 1.87 0.208 Inf 1.46 2.28
6 1.57 0.208 Inf 1.17 1.98
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.2907 0.0426 Inf -6.830 <.0001
StepF1 - StepF3 -0.4175 0.0426 Inf -9.809 <.0001
StepF1 - StepF4 -0.3103 0.0426 Inf -7.291 <.0001
StepF1 - StepF5 -0.3213 0.0426 Inf -7.538 <.0001
StepF1 - StepF6 -0.0238 0.0428 Inf -0.556 0.9937
StepF2 - StepF3 -0.1268 0.0426 Inf -2.979 0.0344
StepF2 - StepF4 -0.0196 0.0426 Inf -0.461 0.9974
StepF2 - StepF5 -0.0306 0.0426 Inf -0.719 0.9798
StepF2 - StepF6 0.2668 0.0428 Inf 6.233 <.0001
StepF3 - StepF4 0.1072 0.0426 Inf 2.518 0.1187
StepF3 - StepF5 0.0962 0.0426 Inf 2.256 0.2123
StepF3 - StepF6 0.3936 0.0428 Inf 9.194 <.0001
StepF4 - StepF5 -0.0110 0.0426 Inf -0.258 0.9998
StepF4 - StepF6 0.2865 0.0428 Inf 6.691 <.0001
StepF5 - StepF6 0.2975 0.0429 Inf 6.940 <.0001
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.2907 0.0426 Inf -6.830 <.0001
StepF1 - StepF3 -0.4175 0.0426 Inf -9.809 <.0001
StepF1 - StepF4 -0.3103 0.0426 Inf -7.291 <.0001
StepF1 - StepF5 -0.3213 0.0426 Inf -7.538 <.0001
StepF1 - StepF6 -0.0238 0.0428 Inf -0.556 0.9937
StepF2 - StepF3 -0.1268 0.0426 Inf -2.979 0.0344
StepF2 - StepF4 -0.0196 0.0426 Inf -0.461 0.9974
StepF2 - StepF5 -0.0306 0.0426 Inf -0.719 0.9798
StepF2 - StepF6 0.2668 0.0428 Inf 6.233 <.0001
StepF3 - StepF4 0.1072 0.0426 Inf 2.518 0.1187
StepF3 - StepF5 0.0962 0.0426 Inf 2.256 0.2123
StepF3 - StepF6 0.3936 0.0428 Inf 9.194 <.0001
StepF4 - StepF5 -0.0110 0.0426 Inf -0.258 0.9998
StepF4 - StepF6 0.2865 0.0428 Inf 6.691 <.0001
StepF5 - StepF6 0.2975 0.0429 Inf 6.940 <.0001
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.291 0.0426 Inf 6.830 <.0001
StepF3 - StepF2 0.127 0.0426 Inf 2.979 0.0087
StepF4 - StepF3 -0.107 0.0426 Inf -2.518 0.0236
StepF5 - StepF4 0.011 0.0426 Inf 0.258 0.7962
StepF6 - StepF5 -0.297 0.0429 Inf -6.940 <.0001
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.291 0.0426 Inf 6.830 <.0001
StepF3 - StepF2 0.127 0.0426 Inf 2.979 0.0087
StepF4 - StepF3 -0.107 0.0426 Inf -2.518 0.0236
StepF5 - StepF4 0.011 0.0426 Inf 0.258 0.7962
StepF6 - StepF5 -0.297 0.0429 Inf -6.940 <.0001
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests .report_step_block(stepwise_12, "2 (12 steps)")
==============================
TRAINING | Block 2 (12 steps) | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 318.7298 11 <2e-16 ***
Accuracy 0.9562 1 0.3281
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.636 0.0715 Inf 0.496 0.776
2 0.831 0.0715 Inf 0.691 0.971
3 0.821 0.0715 Inf 0.680 0.961
4 0.707 0.0715 Inf 0.566 0.847
5 0.702 0.0715 Inf 0.562 0.842
6 0.690 0.0715 Inf 0.550 0.830
7 0.648 0.0715 Inf 0.508 0.789
8 0.641 0.0715 Inf 0.501 0.781
9 0.666 0.0715 Inf 0.526 0.806
10 0.668 0.0715 Inf 0.528 0.808
11 0.616 0.0715 Inf 0.476 0.756
12 0.559 0.0715 Inf 0.419 0.699
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.648 0.0712 Inf 0.508 0.787
2 0.843 0.0712 Inf 0.703 0.983
3 0.832 0.0712 Inf 0.692 0.972
4 0.718 0.0712 Inf 0.578 0.858
5 0.714 0.0712 Inf 0.574 0.853
6 0.701 0.0712 Inf 0.562 0.841
7 0.660 0.0712 Inf 0.520 0.800
8 0.653 0.0712 Inf 0.513 0.792
9 0.677 0.0712 Inf 0.538 0.817
10 0.680 0.0712 Inf 0.540 0.819
11 0.628 0.0712 Inf 0.488 0.767
12 0.571 0.0712 Inf 0.431 0.710
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.19518 0.0206 Inf -9.496 <.0001
StepF1 - StepF3 -0.18430 0.0206 Inf -8.966 <.0001
StepF1 - StepF4 -0.07037 0.0206 Inf -3.423 0.0305
StepF1 - StepF5 -0.06585 0.0206 Inf -3.204 0.0608
StepF1 - StepF6 -0.05362 0.0206 Inf -2.609 0.2744
StepF1 - StepF7 -0.01229 0.0206 Inf -0.598 1.0000
StepF1 - StepF8 -0.00490 0.0206 Inf -0.238 1.0000
StepF1 - StepF9 -0.02950 0.0206 Inf -1.435 0.9567
StepF1 - StepF10 -0.03182 0.0206 Inf -1.548 0.9270
StepF1 - StepF11 0.02016 0.0206 Inf 0.981 0.9981
StepF1 - StepF12 0.07722 0.0206 Inf 3.752 0.0096
StepF2 - StepF3 0.01088 0.0206 Inf 0.529 1.0000
StepF2 - StepF4 0.12481 0.0206 Inf 6.072 <.0001
StepF2 - StepF5 0.12933 0.0206 Inf 6.292 <.0001
StepF2 - StepF6 0.14155 0.0206 Inf 6.887 <.0001
StepF2 - StepF7 0.18289 0.0206 Inf 8.898 <.0001
StepF2 - StepF8 0.19028 0.0206 Inf 9.257 <.0001
StepF2 - StepF9 0.16567 0.0206 Inf 8.060 <.0001
StepF2 - StepF10 0.16335 0.0206 Inf 7.947 <.0001
StepF2 - StepF11 0.21533 0.0206 Inf 10.476 <.0001
StepF2 - StepF12 0.27240 0.0206 Inf 13.237 <.0001
StepF3 - StepF4 0.11393 0.0206 Inf 5.543 <.0001
StepF3 - StepF5 0.11845 0.0206 Inf 5.763 <.0001
StepF3 - StepF6 0.13067 0.0206 Inf 6.357 <.0001
StepF3 - StepF7 0.17201 0.0206 Inf 8.369 <.0001
StepF3 - StepF8 0.17940 0.0206 Inf 8.728 <.0001
StepF3 - StepF9 0.15479 0.0206 Inf 7.531 <.0001
StepF3 - StepF10 0.15248 0.0206 Inf 7.418 <.0001
StepF3 - StepF11 0.20445 0.0206 Inf 9.947 <.0001
StepF3 - StepF12 0.26152 0.0206 Inf 12.708 <.0001
StepF4 - StepF5 0.00452 0.0206 Inf 0.220 1.0000
StepF4 - StepF6 0.01674 0.0206 Inf 0.815 0.9997
StepF4 - StepF7 0.05808 0.0206 Inf 2.826 0.1691
StepF4 - StepF8 0.06547 0.0206 Inf 3.185 0.0642
StepF4 - StepF9 0.04086 0.0206 Inf 1.988 0.7019
StepF4 - StepF10 0.03855 0.0206 Inf 1.875 0.7749
StepF4 - StepF11 0.09052 0.0206 Inf 4.404 0.0007
StepF4 - StepF12 0.14759 0.0206 Inf 7.172 <.0001
StepF5 - StepF6 0.01223 0.0206 Inf 0.595 1.0000
StepF5 - StepF7 0.05356 0.0206 Inf 2.606 0.2760
StepF5 - StepF8 0.06095 0.0206 Inf 2.965 0.1188
StepF5 - StepF9 0.03635 0.0206 Inf 1.768 0.8354
StepF5 - StepF10 0.03403 0.0206 Inf 1.656 0.8881
StepF5 - StepF11 0.08601 0.0206 Inf 4.184 0.0017
StepF5 - StepF12 0.14307 0.0206 Inf 6.952 <.0001
StepF6 - StepF7 0.04134 0.0206 Inf 2.011 0.6860
StepF6 - StepF8 0.04873 0.0206 Inf 2.371 0.4262
StepF6 - StepF9 0.02412 0.0206 Inf 1.173 0.9909
StepF6 - StepF10 0.02180 0.0206 Inf 1.061 0.9962
StepF6 - StepF11 0.07378 0.0206 Inf 3.590 0.0173
StepF6 - StepF12 0.13085 0.0206 Inf 6.358 <.0001
StepF7 - StepF8 0.00739 0.0206 Inf 0.359 1.0000
StepF7 - StepF9 -0.01722 0.0206 Inf -0.838 0.9996
StepF7 - StepF10 -0.01953 0.0206 Inf -0.950 0.9986
StepF7 - StepF11 0.03244 0.0206 Inf 1.578 0.9171
StepF7 - StepF12 0.08951 0.0206 Inf 4.350 0.0008
StepF8 - StepF9 -0.02461 0.0206 Inf -1.197 0.9893
StepF8 - StepF10 -0.02692 0.0206 Inf -1.310 0.9781
StepF8 - StepF11 0.02505 0.0206 Inf 1.219 0.9876
StepF8 - StepF12 0.08212 0.0206 Inf 3.990 0.0038
StepF9 - StepF10 -0.00232 0.0206 Inf -0.113 1.0000
StepF9 - StepF11 0.04966 0.0206 Inf 2.416 0.3948
StepF9 - StepF12 0.10673 0.0206 Inf 5.186 <.0001
StepF10 - StepF11 0.05198 0.0206 Inf 2.529 0.3217
StepF10 - StepF12 0.10904 0.0206 Inf 5.299 <.0001
StepF11 - StepF12 0.05706 0.0206 Inf 2.773 0.1915
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.19518 0.0206 Inf -9.496 <.0001
StepF1 - StepF3 -0.18430 0.0206 Inf -8.966 <.0001
StepF1 - StepF4 -0.07037 0.0206 Inf -3.423 0.0305
StepF1 - StepF5 -0.06585 0.0206 Inf -3.204 0.0608
StepF1 - StepF6 -0.05362 0.0206 Inf -2.609 0.2744
StepF1 - StepF7 -0.01229 0.0206 Inf -0.598 1.0000
StepF1 - StepF8 -0.00490 0.0206 Inf -0.238 1.0000
StepF1 - StepF9 -0.02950 0.0206 Inf -1.435 0.9567
StepF1 - StepF10 -0.03182 0.0206 Inf -1.548 0.9270
StepF1 - StepF11 0.02016 0.0206 Inf 0.981 0.9981
StepF1 - StepF12 0.07722 0.0206 Inf 3.752 0.0096
StepF2 - StepF3 0.01088 0.0206 Inf 0.529 1.0000
StepF2 - StepF4 0.12481 0.0206 Inf 6.072 <.0001
StepF2 - StepF5 0.12933 0.0206 Inf 6.292 <.0001
StepF2 - StepF6 0.14155 0.0206 Inf 6.887 <.0001
StepF2 - StepF7 0.18289 0.0206 Inf 8.898 <.0001
StepF2 - StepF8 0.19028 0.0206 Inf 9.257 <.0001
StepF2 - StepF9 0.16567 0.0206 Inf 8.060 <.0001
StepF2 - StepF10 0.16335 0.0206 Inf 7.947 <.0001
StepF2 - StepF11 0.21533 0.0206 Inf 10.476 <.0001
StepF2 - StepF12 0.27240 0.0206 Inf 13.237 <.0001
StepF3 - StepF4 0.11393 0.0206 Inf 5.543 <.0001
StepF3 - StepF5 0.11845 0.0206 Inf 5.763 <.0001
StepF3 - StepF6 0.13067 0.0206 Inf 6.357 <.0001
StepF3 - StepF7 0.17201 0.0206 Inf 8.369 <.0001
StepF3 - StepF8 0.17940 0.0206 Inf 8.728 <.0001
StepF3 - StepF9 0.15479 0.0206 Inf 7.531 <.0001
StepF3 - StepF10 0.15248 0.0206 Inf 7.418 <.0001
StepF3 - StepF11 0.20445 0.0206 Inf 9.947 <.0001
StepF3 - StepF12 0.26152 0.0206 Inf 12.708 <.0001
StepF4 - StepF5 0.00452 0.0206 Inf 0.220 1.0000
StepF4 - StepF6 0.01674 0.0206 Inf 0.815 0.9997
StepF4 - StepF7 0.05808 0.0206 Inf 2.826 0.1691
StepF4 - StepF8 0.06547 0.0206 Inf 3.185 0.0642
StepF4 - StepF9 0.04086 0.0206 Inf 1.988 0.7019
StepF4 - StepF10 0.03855 0.0206 Inf 1.875 0.7749
StepF4 - StepF11 0.09052 0.0206 Inf 4.404 0.0007
StepF4 - StepF12 0.14759 0.0206 Inf 7.172 <.0001
StepF5 - StepF6 0.01223 0.0206 Inf 0.595 1.0000
StepF5 - StepF7 0.05356 0.0206 Inf 2.606 0.2760
StepF5 - StepF8 0.06095 0.0206 Inf 2.965 0.1188
StepF5 - StepF9 0.03635 0.0206 Inf 1.768 0.8354
StepF5 - StepF10 0.03403 0.0206 Inf 1.656 0.8881
StepF5 - StepF11 0.08601 0.0206 Inf 4.184 0.0017
StepF5 - StepF12 0.14307 0.0206 Inf 6.952 <.0001
StepF6 - StepF7 0.04134 0.0206 Inf 2.011 0.6860
StepF6 - StepF8 0.04873 0.0206 Inf 2.371 0.4262
StepF6 - StepF9 0.02412 0.0206 Inf 1.173 0.9909
StepF6 - StepF10 0.02180 0.0206 Inf 1.061 0.9962
StepF6 - StepF11 0.07378 0.0206 Inf 3.590 0.0173
StepF6 - StepF12 0.13085 0.0206 Inf 6.358 <.0001
StepF7 - StepF8 0.00739 0.0206 Inf 0.359 1.0000
StepF7 - StepF9 -0.01722 0.0206 Inf -0.838 0.9996
StepF7 - StepF10 -0.01953 0.0206 Inf -0.950 0.9986
StepF7 - StepF11 0.03244 0.0206 Inf 1.578 0.9171
StepF7 - StepF12 0.08951 0.0206 Inf 4.350 0.0008
StepF8 - StepF9 -0.02461 0.0206 Inf -1.197 0.9893
StepF8 - StepF10 -0.02692 0.0206 Inf -1.310 0.9781
StepF8 - StepF11 0.02505 0.0206 Inf 1.219 0.9876
StepF8 - StepF12 0.08212 0.0206 Inf 3.990 0.0038
StepF9 - StepF10 -0.00232 0.0206 Inf -0.113 1.0000
StepF9 - StepF11 0.04966 0.0206 Inf 2.416 0.3948
StepF9 - StepF12 0.10673 0.0206 Inf 5.186 <.0001
StepF10 - StepF11 0.05198 0.0206 Inf 2.529 0.3217
StepF10 - StepF12 0.10904 0.0206 Inf 5.299 <.0001
StepF11 - StepF12 0.05706 0.0206 Inf 2.773 0.1915
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.19518 0.0206 Inf 9.496 <.0001
StepF3 - StepF2 -0.01088 0.0206 Inf -0.529 1.0000
StepF4 - StepF3 -0.11393 0.0206 Inf -5.543 <.0001
StepF5 - StepF4 -0.00452 0.0206 Inf -0.220 1.0000
StepF6 - StepF5 -0.01223 0.0206 Inf -0.595 1.0000
StepF7 - StepF6 -0.04134 0.0206 Inf -2.011 0.3102
StepF8 - StepF7 -0.00739 0.0206 Inf -0.359 1.0000
StepF9 - StepF8 0.02461 0.0206 Inf 1.197 1.0000
StepF10 - StepF9 0.00232 0.0206 Inf 0.113 1.0000
StepF11 - StepF10 -0.05198 0.0206 Inf -2.529 0.0916
StepF12 - StepF11 -0.05706 0.0206 Inf -2.773 0.0500
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.19518 0.0206 Inf 9.496 <.0001
StepF3 - StepF2 -0.01088 0.0206 Inf -0.529 1.0000
StepF4 - StepF3 -0.11393 0.0206 Inf -5.543 <.0001
StepF5 - StepF4 -0.00452 0.0206 Inf -0.220 1.0000
StepF6 - StepF5 -0.01223 0.0206 Inf -0.595 1.0000
StepF7 - StepF6 -0.04134 0.0206 Inf -2.011 0.3102
StepF8 - StepF7 -0.00739 0.0206 Inf -0.359 1.0000
StepF9 - StepF8 0.02461 0.0206 Inf 1.197 1.0000
StepF10 - StepF9 0.00232 0.0206 Inf 0.113 1.0000
StepF11 - StepF10 -0.05198 0.0206 Inf -2.529 0.0916
StepF12 - StepF11 -0.05706 0.0206 Inf -2.773 0.0500
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests
==============================
TRAINING | Block 2 (12 steps) | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 194.8659 11 <2e-16 ***
Accuracy 1.9438 1 0.1633
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.806 0.0840 Inf 0.641 0.970
2 0.793 0.0840 Inf 0.628 0.957
3 0.886 0.0840 Inf 0.721 1.050
4 0.789 0.0840 Inf 0.625 0.954
5 0.714 0.0840 Inf 0.550 0.879
6 0.739 0.0840 Inf 0.574 0.904
7 0.817 0.0840 Inf 0.653 0.982
8 0.702 0.0840 Inf 0.537 0.866
9 0.720 0.0840 Inf 0.555 0.884
10 0.719 0.0840 Inf 0.554 0.883
11 0.686 0.0840 Inf 0.521 0.851
12 0.633 0.0840 Inf 0.469 0.798
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.824 0.0837 Inf 0.660 0.988
2 0.811 0.0837 Inf 0.647 0.975
3 0.904 0.0837 Inf 0.740 1.068
4 0.808 0.0837 Inf 0.644 0.972
5 0.733 0.0837 Inf 0.569 0.897
6 0.757 0.0837 Inf 0.593 0.922
7 0.836 0.0837 Inf 0.672 1.000
8 0.720 0.0837 Inf 0.556 0.884
9 0.738 0.0837 Inf 0.574 0.902
10 0.737 0.0837 Inf 0.573 0.901
11 0.704 0.0837 Inf 0.540 0.868
12 0.652 0.0837 Inf 0.488 0.816
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.01283 0.0232 Inf 0.552 1.0000
StepF1 - StepF3 -0.08001 0.0232 Inf -3.444 0.0285
StepF1 - StepF4 0.01641 0.0232 Inf 0.706 0.9999
StepF1 - StepF5 0.09111 0.0232 Inf 3.922 0.0050
StepF1 - StepF6 0.06651 0.0232 Inf 2.863 0.1544
StepF1 - StepF7 -0.01179 0.0232 Inf -0.507 1.0000
StepF1 - StepF8 0.10382 0.0232 Inf 4.469 0.0005
StepF1 - StepF9 0.08569 0.0232 Inf 3.689 0.0121
StepF1 - StepF10 0.08685 0.0232 Inf 3.738 0.0101
StepF1 - StepF11 0.11963 0.0232 Inf 5.149 <.0001
StepF1 - StepF12 0.17213 0.0233 Inf 7.400 <.0001
StepF2 - StepF3 -0.09284 0.0232 Inf -3.996 0.0037
StepF2 - StepF4 0.00357 0.0232 Inf 0.154 1.0000
StepF2 - StepF5 0.07828 0.0232 Inf 3.369 0.0363
StepF2 - StepF6 0.05367 0.0232 Inf 2.310 0.4690
StepF2 - StepF7 -0.02462 0.0232 Inf -1.060 0.9962
StepF2 - StepF8 0.09098 0.0232 Inf 3.916 0.0051
StepF2 - StepF9 0.07286 0.0232 Inf 3.136 0.0741
StepF2 - StepF10 0.07401 0.0232 Inf 3.186 0.0641
StepF2 - StepF11 0.10680 0.0232 Inf 4.597 0.0003
StepF2 - StepF12 0.15930 0.0233 Inf 6.849 <.0001
StepF3 - StepF4 0.09642 0.0232 Inf 4.150 0.0020
StepF3 - StepF5 0.17112 0.0232 Inf 7.366 <.0001
StepF3 - StepF6 0.14652 0.0232 Inf 6.307 <.0001
StepF3 - StepF7 0.06822 0.0232 Inf 2.937 0.1281
StepF3 - StepF8 0.18382 0.0232 Inf 7.913 <.0001
StepF3 - StepF9 0.16570 0.0232 Inf 7.133 <.0001
StepF3 - StepF10 0.16685 0.0232 Inf 7.182 <.0001
StepF3 - StepF11 0.19964 0.0232 Inf 8.593 <.0001
StepF3 - StepF12 0.25214 0.0233 Inf 10.840 <.0001
StepF4 - StepF5 0.07471 0.0232 Inf 3.216 0.0586
StepF4 - StepF6 0.05010 0.0232 Inf 2.157 0.5816
StepF4 - StepF7 -0.02819 0.0232 Inf -1.214 0.9880
StepF4 - StepF8 0.08741 0.0232 Inf 3.762 0.0092
StepF4 - StepF9 0.06929 0.0232 Inf 2.982 0.1136
StepF4 - StepF10 0.07044 0.0232 Inf 3.032 0.0994
StepF4 - StepF11 0.10322 0.0232 Inf 4.443 0.0005
StepF4 - StepF12 0.15572 0.0233 Inf 6.695 <.0001
StepF5 - StepF6 -0.02461 0.0232 Inf -1.059 0.9962
StepF5 - StepF7 -0.10290 0.0232 Inf -4.429 0.0006
StepF5 - StepF8 0.01270 0.0232 Inf 0.547 1.0000
StepF5 - StepF9 -0.00542 0.0232 Inf -0.233 1.0000
StepF5 - StepF10 -0.00427 0.0232 Inf -0.184 1.0000
StepF5 - StepF11 0.02852 0.0232 Inf 1.227 0.9869
StepF5 - StepF12 0.08102 0.0233 Inf 3.483 0.0249
StepF6 - StepF7 -0.07829 0.0232 Inf -3.370 0.0362
StepF6 - StepF8 0.03731 0.0232 Inf 1.606 0.9074
StepF6 - StepF9 0.01919 0.0232 Inf 0.826 0.9996
StepF6 - StepF10 0.02034 0.0232 Inf 0.875 0.9993
StepF6 - StepF11 0.05312 0.0232 Inf 2.287 0.4862
StepF6 - StepF12 0.10562 0.0233 Inf 4.541 0.0003
StepF7 - StepF8 0.11560 0.0232 Inf 4.976 <.0001
StepF7 - StepF9 0.09748 0.0232 Inf 4.196 0.0016
StepF7 - StepF10 0.09863 0.0232 Inf 4.246 0.0013
StepF7 - StepF11 0.13141 0.0232 Inf 5.657 <.0001
StepF7 - StepF12 0.18392 0.0233 Inf 7.907 <.0001
StepF8 - StepF9 -0.01812 0.0232 Inf -0.780 0.9998
StepF8 - StepF10 -0.01697 0.0232 Inf -0.730 0.9999
StepF8 - StepF11 0.01581 0.0232 Inf 0.681 0.9999
StepF8 - StepF12 0.06832 0.0233 Inf 2.937 0.1279
StepF9 - StepF10 0.00115 0.0232 Inf 0.050 1.0000
StepF9 - StepF11 0.03393 0.0232 Inf 1.461 0.9510
StepF9 - StepF12 0.08644 0.0233 Inf 3.716 0.0110
StepF10 - StepF11 0.03278 0.0232 Inf 1.411 0.9617
StepF10 - StepF12 0.08529 0.0233 Inf 3.667 0.0131
StepF11 - StepF12 0.05250 0.0233 Inf 2.257 0.5075
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.01283 0.0232 Inf 0.552 1.0000
StepF1 - StepF3 -0.08001 0.0232 Inf -3.444 0.0285
StepF1 - StepF4 0.01641 0.0232 Inf 0.706 0.9999
StepF1 - StepF5 0.09111 0.0232 Inf 3.922 0.0050
StepF1 - StepF6 0.06651 0.0232 Inf 2.863 0.1544
StepF1 - StepF7 -0.01179 0.0232 Inf -0.507 1.0000
StepF1 - StepF8 0.10382 0.0232 Inf 4.469 0.0005
StepF1 - StepF9 0.08569 0.0232 Inf 3.689 0.0121
StepF1 - StepF10 0.08685 0.0232 Inf 3.738 0.0101
StepF1 - StepF11 0.11963 0.0232 Inf 5.149 <.0001
StepF1 - StepF12 0.17213 0.0233 Inf 7.400 <.0001
StepF2 - StepF3 -0.09284 0.0232 Inf -3.996 0.0037
StepF2 - StepF4 0.00357 0.0232 Inf 0.154 1.0000
StepF2 - StepF5 0.07828 0.0232 Inf 3.369 0.0363
StepF2 - StepF6 0.05367 0.0232 Inf 2.310 0.4690
StepF2 - StepF7 -0.02462 0.0232 Inf -1.060 0.9962
StepF2 - StepF8 0.09098 0.0232 Inf 3.916 0.0051
StepF2 - StepF9 0.07286 0.0232 Inf 3.136 0.0741
StepF2 - StepF10 0.07401 0.0232 Inf 3.186 0.0641
StepF2 - StepF11 0.10680 0.0232 Inf 4.597 0.0003
StepF2 - StepF12 0.15930 0.0233 Inf 6.849 <.0001
StepF3 - StepF4 0.09642 0.0232 Inf 4.150 0.0020
StepF3 - StepF5 0.17112 0.0232 Inf 7.366 <.0001
StepF3 - StepF6 0.14652 0.0232 Inf 6.307 <.0001
StepF3 - StepF7 0.06822 0.0232 Inf 2.937 0.1281
StepF3 - StepF8 0.18382 0.0232 Inf 7.913 <.0001
StepF3 - StepF9 0.16570 0.0232 Inf 7.133 <.0001
StepF3 - StepF10 0.16685 0.0232 Inf 7.182 <.0001
StepF3 - StepF11 0.19964 0.0232 Inf 8.593 <.0001
StepF3 - StepF12 0.25214 0.0233 Inf 10.840 <.0001
StepF4 - StepF5 0.07471 0.0232 Inf 3.216 0.0586
StepF4 - StepF6 0.05010 0.0232 Inf 2.157 0.5816
StepF4 - StepF7 -0.02819 0.0232 Inf -1.214 0.9880
StepF4 - StepF8 0.08741 0.0232 Inf 3.762 0.0092
StepF4 - StepF9 0.06929 0.0232 Inf 2.982 0.1136
StepF4 - StepF10 0.07044 0.0232 Inf 3.032 0.0994
StepF4 - StepF11 0.10322 0.0232 Inf 4.443 0.0005
StepF4 - StepF12 0.15572 0.0233 Inf 6.695 <.0001
StepF5 - StepF6 -0.02461 0.0232 Inf -1.059 0.9962
StepF5 - StepF7 -0.10290 0.0232 Inf -4.429 0.0006
StepF5 - StepF8 0.01270 0.0232 Inf 0.547 1.0000
StepF5 - StepF9 -0.00542 0.0232 Inf -0.233 1.0000
StepF5 - StepF10 -0.00427 0.0232 Inf -0.184 1.0000
StepF5 - StepF11 0.02852 0.0232 Inf 1.227 0.9869
StepF5 - StepF12 0.08102 0.0233 Inf 3.483 0.0249
StepF6 - StepF7 -0.07829 0.0232 Inf -3.370 0.0362
StepF6 - StepF8 0.03731 0.0232 Inf 1.606 0.9074
StepF6 - StepF9 0.01919 0.0232 Inf 0.826 0.9996
StepF6 - StepF10 0.02034 0.0232 Inf 0.875 0.9993
StepF6 - StepF11 0.05312 0.0232 Inf 2.287 0.4862
StepF6 - StepF12 0.10562 0.0233 Inf 4.541 0.0003
StepF7 - StepF8 0.11560 0.0232 Inf 4.976 <.0001
StepF7 - StepF9 0.09748 0.0232 Inf 4.196 0.0016
StepF7 - StepF10 0.09863 0.0232 Inf 4.246 0.0013
StepF7 - StepF11 0.13141 0.0232 Inf 5.657 <.0001
StepF7 - StepF12 0.18392 0.0233 Inf 7.907 <.0001
StepF8 - StepF9 -0.01812 0.0232 Inf -0.780 0.9998
StepF8 - StepF10 -0.01697 0.0232 Inf -0.730 0.9999
StepF8 - StepF11 0.01581 0.0232 Inf 0.681 0.9999
StepF8 - StepF12 0.06832 0.0233 Inf 2.937 0.1279
StepF9 - StepF10 0.00115 0.0232 Inf 0.050 1.0000
StepF9 - StepF11 0.03393 0.0232 Inf 1.461 0.9510
StepF9 - StepF12 0.08644 0.0233 Inf 3.716 0.0110
StepF10 - StepF11 0.03278 0.0232 Inf 1.411 0.9617
StepF10 - StepF12 0.08529 0.0233 Inf 3.667 0.0131
StepF11 - StepF12 0.05250 0.0233 Inf 2.257 0.5075
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.01283 0.0232 Inf -0.552 1.0000
StepF3 - StepF2 0.09284 0.0232 Inf 3.996 0.0006
StepF4 - StepF3 -0.09642 0.0232 Inf -4.150 0.0003
StepF5 - StepF4 -0.07471 0.0232 Inf -3.216 0.0091
StepF6 - StepF5 0.02461 0.0232 Inf 1.059 1.0000
StepF7 - StepF6 0.07829 0.0232 Inf 3.370 0.0060
StepF8 - StepF7 -0.11560 0.0232 Inf -4.976 <.0001
StepF9 - StepF8 0.01812 0.0232 Inf 0.780 1.0000
StepF10 - StepF9 -0.00115 0.0232 Inf -0.050 1.0000
StepF11 - StepF10 -0.03278 0.0232 Inf -1.411 0.7911
StepF12 - StepF11 -0.05250 0.0233 Inf -2.257 0.1440
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.01283 0.0232 Inf -0.552 1.0000
StepF3 - StepF2 0.09284 0.0232 Inf 3.996 0.0006
StepF4 - StepF3 -0.09642 0.0232 Inf -4.150 0.0003
StepF5 - StepF4 -0.07471 0.0232 Inf -3.216 0.0091
StepF6 - StepF5 0.02461 0.0232 Inf 1.059 1.0000
StepF7 - StepF6 0.07829 0.0232 Inf 3.370 0.0060
StepF8 - StepF7 -0.11560 0.0232 Inf -4.976 <.0001
StepF9 - StepF8 0.01812 0.0232 Inf 0.780 1.0000
StepF10 - StepF9 -0.00115 0.0232 Inf -0.050 1.0000
StepF11 - StepF10 -0.03278 0.0232 Inf -1.411 0.7911
StepF12 - StepF11 -0.05250 0.0233 Inf -2.257 0.1440
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests
==============================
TRAINING | Block 2 (12 steps) | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 228.3268 11 <2e-16 ***
Accuracy 1.0719 1 0.3005
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.41 0.138 Inf 1.141 1.68
2 1.66 0.138 Inf 1.386 1.93
3 1.64 0.138 Inf 1.367 1.91
4 1.52 0.138 Inf 1.247 1.79
5 1.51 0.138 Inf 1.241 1.78
6 1.38 0.138 Inf 1.109 1.65
7 1.47 0.138 Inf 1.199 1.74
8 1.38 0.138 Inf 1.108 1.65
9 1.39 0.138 Inf 1.117 1.66
10 1.39 0.138 Inf 1.117 1.66
11 1.35 0.138 Inf 1.081 1.62
12 1.18 0.138 Inf 0.910 1.45
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.44 0.138 Inf 1.167 1.71
2 1.68 0.138 Inf 1.411 1.95
3 1.66 0.138 Inf 1.392 1.93
4 1.54 0.138 Inf 1.272 1.81
5 1.54 0.138 Inf 1.267 1.81
6 1.40 0.138 Inf 1.135 1.68
7 1.49 0.138 Inf 1.225 1.77
8 1.40 0.138 Inf 1.133 1.67
9 1.41 0.138 Inf 1.142 1.68
10 1.41 0.138 Inf 1.143 1.68
11 1.38 0.138 Inf 1.106 1.65
12 1.21 0.138 Inf 0.936 1.48
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.244382 0.0404 Inf -6.051 <.0001
StepF1 - StepF3 -0.225688 0.0404 Inf -5.588 <.0001
StepF1 - StepF4 -0.105241 0.0404 Inf -2.606 0.2760
StepF1 - StepF5 -0.100001 0.0404 Inf -2.476 0.3549
StepF1 - StepF6 0.032041 0.0404 Inf 0.793 0.9997
StepF1 - StepF7 -0.057797 0.0404 Inf -1.431 0.9576
StepF1 - StepF8 0.033679 0.0404 Inf 0.834 0.9996
StepF1 - StepF9 0.024347 0.0404 Inf 0.603 1.0000
StepF1 - StepF10 0.024180 0.0404 Inf 0.599 1.0000
StepF1 - StepF11 0.060822 0.0404 Inf 1.506 0.9394
StepF1 - StepF12 0.230900 0.0404 Inf 5.711 <.0001
StepF2 - StepF3 0.018694 0.0404 Inf 0.463 1.0000
StepF2 - StepF4 0.139141 0.0404 Inf 3.445 0.0283
StepF2 - StepF5 0.144381 0.0404 Inf 3.575 0.0182
StepF2 - StepF6 0.276422 0.0404 Inf 6.845 <.0001
StepF2 - StepF7 0.186584 0.0404 Inf 4.620 0.0002
StepF2 - StepF8 0.278061 0.0404 Inf 6.885 <.0001
StepF2 - StepF9 0.268728 0.0404 Inf 6.654 <.0001
StepF2 - StepF10 0.268562 0.0404 Inf 6.650 <.0001
StepF2 - StepF11 0.305203 0.0404 Inf 7.557 <.0001
StepF2 - StepF12 0.475282 0.0404 Inf 11.755 <.0001
StepF3 - StepF4 0.120447 0.0404 Inf 2.983 0.1136
StepF3 - StepF5 0.125687 0.0404 Inf 3.112 0.0794
StepF3 - StepF6 0.257729 0.0404 Inf 6.382 <.0001
StepF3 - StepF7 0.167891 0.0404 Inf 4.157 0.0019
StepF3 - StepF8 0.259367 0.0404 Inf 6.422 <.0001
StepF3 - StepF9 0.250034 0.0404 Inf 6.191 <.0001
StepF3 - StepF10 0.249868 0.0404 Inf 6.187 <.0001
StepF3 - StepF11 0.286509 0.0404 Inf 7.095 <.0001
StepF3 - StepF12 0.456588 0.0404 Inf 11.293 <.0001
StepF4 - StepF5 0.005240 0.0404 Inf 0.130 1.0000
StepF4 - StepF6 0.137281 0.0404 Inf 3.399 0.0330
StepF4 - StepF7 0.047443 0.0404 Inf 1.175 0.9908
StepF4 - StepF8 0.138920 0.0404 Inf 3.440 0.0288
StepF4 - StepF9 0.129587 0.0404 Inf 3.209 0.0599
StepF4 - StepF10 0.129421 0.0404 Inf 3.205 0.0606
StepF4 - StepF11 0.166062 0.0404 Inf 4.112 0.0023
StepF4 - StepF12 0.336141 0.0404 Inf 8.314 <.0001
StepF5 - StepF6 0.132041 0.0404 Inf 3.270 0.0498
StepF5 - StepF7 0.042203 0.0404 Inf 1.045 0.9966
StepF5 - StepF8 0.133680 0.0404 Inf 3.310 0.0439
StepF5 - StepF9 0.124347 0.0404 Inf 3.079 0.0872
StepF5 - StepF10 0.124181 0.0404 Inf 3.075 0.0882
StepF5 - StepF11 0.160822 0.0404 Inf 3.982 0.0039
StepF5 - StepF12 0.330901 0.0404 Inf 8.184 <.0001
StepF6 - StepF7 -0.089838 0.0404 Inf -2.225 0.5315
StepF6 - StepF8 0.001638 0.0404 Inf 0.041 1.0000
StepF6 - StepF9 -0.007694 0.0404 Inf -0.191 1.0000
StepF6 - StepF10 -0.007861 0.0404 Inf -0.195 1.0000
StepF6 - StepF11 0.028781 0.0404 Inf 0.713 0.9999
StepF6 - StepF12 0.198859 0.0404 Inf 4.918 0.0001
StepF7 - StepF8 0.091477 0.0404 Inf 2.265 0.5018
StepF7 - StepF9 0.082144 0.0404 Inf 2.034 0.6700
StepF7 - StepF10 0.081977 0.0404 Inf 2.030 0.6729
StepF7 - StepF11 0.118619 0.0404 Inf 2.937 0.1279
StepF7 - StepF12 0.288697 0.0404 Inf 7.140 <.0001
StepF8 - StepF9 -0.009333 0.0404 Inf -0.231 1.0000
StepF8 - StepF10 -0.009499 0.0404 Inf -0.235 1.0000
StepF8 - StepF11 0.027142 0.0404 Inf 0.672 0.9999
StepF8 - StepF12 0.197221 0.0404 Inf 4.878 0.0001
StepF9 - StepF10 -0.000166 0.0404 Inf -0.004 1.0000
StepF9 - StepF11 0.036475 0.0404 Inf 0.903 0.9991
StepF9 - StepF12 0.206554 0.0404 Inf 5.109 <.0001
StepF10 - StepF11 0.036641 0.0404 Inf 0.907 0.9991
StepF10 - StepF12 0.206720 0.0404 Inf 5.113 <.0001
StepF11 - StepF12 0.170078 0.0404 Inf 4.206 0.0016
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.244382 0.0404 Inf -6.051 <.0001
StepF1 - StepF3 -0.225688 0.0404 Inf -5.588 <.0001
StepF1 - StepF4 -0.105241 0.0404 Inf -2.606 0.2760
StepF1 - StepF5 -0.100001 0.0404 Inf -2.476 0.3549
StepF1 - StepF6 0.032041 0.0404 Inf 0.793 0.9997
StepF1 - StepF7 -0.057797 0.0404 Inf -1.431 0.9576
StepF1 - StepF8 0.033679 0.0404 Inf 0.834 0.9996
StepF1 - StepF9 0.024347 0.0404 Inf 0.603 1.0000
StepF1 - StepF10 0.024180 0.0404 Inf 0.599 1.0000
StepF1 - StepF11 0.060822 0.0404 Inf 1.506 0.9394
StepF1 - StepF12 0.230900 0.0404 Inf 5.711 <.0001
StepF2 - StepF3 0.018694 0.0404 Inf 0.463 1.0000
StepF2 - StepF4 0.139141 0.0404 Inf 3.445 0.0283
StepF2 - StepF5 0.144381 0.0404 Inf 3.575 0.0182
StepF2 - StepF6 0.276422 0.0404 Inf 6.845 <.0001
StepF2 - StepF7 0.186584 0.0404 Inf 4.620 0.0002
StepF2 - StepF8 0.278061 0.0404 Inf 6.885 <.0001
StepF2 - StepF9 0.268728 0.0404 Inf 6.654 <.0001
StepF2 - StepF10 0.268562 0.0404 Inf 6.650 <.0001
StepF2 - StepF11 0.305203 0.0404 Inf 7.557 <.0001
StepF2 - StepF12 0.475282 0.0404 Inf 11.755 <.0001
StepF3 - StepF4 0.120447 0.0404 Inf 2.983 0.1136
StepF3 - StepF5 0.125687 0.0404 Inf 3.112 0.0794
StepF3 - StepF6 0.257729 0.0404 Inf 6.382 <.0001
StepF3 - StepF7 0.167891 0.0404 Inf 4.157 0.0019
StepF3 - StepF8 0.259367 0.0404 Inf 6.422 <.0001
StepF3 - StepF9 0.250034 0.0404 Inf 6.191 <.0001
StepF3 - StepF10 0.249868 0.0404 Inf 6.187 <.0001
StepF3 - StepF11 0.286509 0.0404 Inf 7.095 <.0001
StepF3 - StepF12 0.456588 0.0404 Inf 11.293 <.0001
StepF4 - StepF5 0.005240 0.0404 Inf 0.130 1.0000
StepF4 - StepF6 0.137281 0.0404 Inf 3.399 0.0330
StepF4 - StepF7 0.047443 0.0404 Inf 1.175 0.9908
StepF4 - StepF8 0.138920 0.0404 Inf 3.440 0.0288
StepF4 - StepF9 0.129587 0.0404 Inf 3.209 0.0599
StepF4 - StepF10 0.129421 0.0404 Inf 3.205 0.0606
StepF4 - StepF11 0.166062 0.0404 Inf 4.112 0.0023
StepF4 - StepF12 0.336141 0.0404 Inf 8.314 <.0001
StepF5 - StepF6 0.132041 0.0404 Inf 3.270 0.0498
StepF5 - StepF7 0.042203 0.0404 Inf 1.045 0.9966
StepF5 - StepF8 0.133680 0.0404 Inf 3.310 0.0439
StepF5 - StepF9 0.124347 0.0404 Inf 3.079 0.0872
StepF5 - StepF10 0.124181 0.0404 Inf 3.075 0.0882
StepF5 - StepF11 0.160822 0.0404 Inf 3.982 0.0039
StepF5 - StepF12 0.330901 0.0404 Inf 8.184 <.0001
StepF6 - StepF7 -0.089838 0.0404 Inf -2.225 0.5315
StepF6 - StepF8 0.001638 0.0404 Inf 0.041 1.0000
StepF6 - StepF9 -0.007694 0.0404 Inf -0.191 1.0000
StepF6 - StepF10 -0.007861 0.0404 Inf -0.195 1.0000
StepF6 - StepF11 0.028781 0.0404 Inf 0.713 0.9999
StepF6 - StepF12 0.198859 0.0404 Inf 4.918 0.0001
StepF7 - StepF8 0.091477 0.0404 Inf 2.265 0.5018
StepF7 - StepF9 0.082144 0.0404 Inf 2.034 0.6700
StepF7 - StepF10 0.081977 0.0404 Inf 2.030 0.6729
StepF7 - StepF11 0.118619 0.0404 Inf 2.937 0.1279
StepF7 - StepF12 0.288697 0.0404 Inf 7.140 <.0001
StepF8 - StepF9 -0.009333 0.0404 Inf -0.231 1.0000
StepF8 - StepF10 -0.009499 0.0404 Inf -0.235 1.0000
StepF8 - StepF11 0.027142 0.0404 Inf 0.672 0.9999
StepF8 - StepF12 0.197221 0.0404 Inf 4.878 0.0001
StepF9 - StepF10 -0.000166 0.0404 Inf -0.004 1.0000
StepF9 - StepF11 0.036475 0.0404 Inf 0.903 0.9991
StepF9 - StepF12 0.206554 0.0404 Inf 5.109 <.0001
StepF10 - StepF11 0.036641 0.0404 Inf 0.907 0.9991
StepF10 - StepF12 0.206720 0.0404 Inf 5.113 <.0001
StepF11 - StepF12 0.170078 0.0404 Inf 4.206 0.0016
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.244381 0.0404 Inf 6.051 <.0001
StepF3 - StepF2 -0.018694 0.0404 Inf -0.463 1.0000
StepF4 - StepF3 -0.120447 0.0404 Inf -2.983 0.0229
StepF5 - StepF4 -0.005240 0.0404 Inf -0.130 1.0000
StepF6 - StepF5 -0.132041 0.0404 Inf -3.270 0.0097
StepF7 - StepF6 0.089838 0.0404 Inf 2.225 0.1645
StepF8 - StepF7 -0.091477 0.0404 Inf -2.265 0.1645
StepF9 - StepF8 0.009333 0.0404 Inf 0.231 1.0000
StepF10 - StepF9 0.000166 0.0404 Inf 0.004 1.0000
StepF11 - StepF10 -0.036641 0.0404 Inf -0.907 1.0000
StepF12 - StepF11 -0.170079 0.0404 Inf -4.206 0.0003
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.244381 0.0404 Inf 6.051 <.0001
StepF3 - StepF2 -0.018694 0.0404 Inf -0.463 1.0000
StepF4 - StepF3 -0.120447 0.0404 Inf -2.983 0.0229
StepF5 - StepF4 -0.005240 0.0404 Inf -0.130 1.0000
StepF6 - StepF5 -0.132041 0.0404 Inf -3.270 0.0097
StepF7 - StepF6 0.089838 0.0404 Inf 2.225 0.1645
StepF8 - StepF7 -0.091477 0.0404 Inf -2.265 0.1645
StepF9 - StepF8 0.009333 0.0404 Inf 0.231 1.0000
StepF10 - StepF9 0.000166 0.0404 Inf 0.004 1.0000
StepF11 - StepF10 -0.036641 0.0404 Inf -0.907 1.0000
StepF12 - StepF11 -0.170079 0.0404 Inf -4.206 0.0003
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests .report_step_block(stepwise_18, "3 (18 steps)")
==============================
TRAINING | Block 3 (18 steps) | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 164.7997 17 <2e-16 ***
Accuracy 0.1116 1 0.7384
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.568 0.0477 Inf 0.475 0.662
2 0.605 0.0477 Inf 0.511 0.698
3 0.618 0.0477 Inf 0.524 0.711
4 0.584 0.0477 Inf 0.490 0.678
5 0.575 0.0477 Inf 0.481 0.668
6 0.588 0.0477 Inf 0.494 0.681
7 0.585 0.0477 Inf 0.491 0.678
8 0.559 0.0477 Inf 0.466 0.653
9 0.562 0.0477 Inf 0.469 0.656
10 0.562 0.0477 Inf 0.469 0.656
11 0.535 0.0477 Inf 0.442 0.629
12 0.498 0.0477 Inf 0.405 0.592
13 0.491 0.0477 Inf 0.397 0.584
14 0.541 0.0477 Inf 0.448 0.635
15 0.529 0.0477 Inf 0.435 0.622
16 0.534 0.0477 Inf 0.440 0.627
17 0.514 0.0477 Inf 0.420 0.607
18 0.513 0.0477 Inf 0.420 0.607
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.566 0.0477 Inf 0.472 0.659
2 0.602 0.0477 Inf 0.509 0.696
3 0.615 0.0477 Inf 0.522 0.709
4 0.581 0.0477 Inf 0.488 0.675
5 0.572 0.0477 Inf 0.479 0.666
6 0.585 0.0477 Inf 0.492 0.678
7 0.582 0.0477 Inf 0.488 0.675
8 0.557 0.0477 Inf 0.463 0.650
9 0.560 0.0477 Inf 0.466 0.653
10 0.560 0.0477 Inf 0.466 0.653
11 0.533 0.0477 Inf 0.439 0.626
12 0.496 0.0477 Inf 0.402 0.589
13 0.488 0.0477 Inf 0.394 0.581
14 0.539 0.0477 Inf 0.445 0.632
15 0.526 0.0477 Inf 0.433 0.620
16 0.531 0.0477 Inf 0.438 0.624
17 0.511 0.0477 Inf 0.417 0.604
18 0.511 0.0477 Inf 0.417 0.604
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.036708 0.0165 Inf -2.230 0.7338
StepF1 - StepF3 -0.049497 0.0165 Inf -3.006 0.1967
StepF1 - StepF4 -0.015775 0.0165 Inf -0.958 1.0000
StepF1 - StepF5 -0.006471 0.0165 Inf -0.393 1.0000
StepF1 - StepF6 -0.019362 0.0165 Inf -1.176 0.9995
StepF1 - StepF7 -0.016356 0.0165 Inf -0.993 0.9999
StepF1 - StepF8 0.009001 0.0165 Inf 0.547 1.0000
StepF1 - StepF9 0.005877 0.0165 Inf 0.357 1.0000
StepF1 - StepF10 0.005905 0.0165 Inf 0.359 1.0000
StepF1 - StepF11 0.032871 0.0165 Inf 1.997 0.8715
StepF1 - StepF12 0.069725 0.0165 Inf 4.235 0.0030
StepF1 - StepF13 0.077649 0.0165 Inf 4.716 0.0003
StepF1 - StepF14 0.026770 0.0165 Inf 1.626 0.9786
StepF1 - StepF15 0.039230 0.0165 Inf 2.383 0.6212
StepF1 - StepF16 0.034602 0.0165 Inf 2.102 0.8158
StepF1 - StepF17 0.054680 0.0165 Inf 3.321 0.0840
StepF1 - StepF18 0.054816 0.0165 Inf 3.326 0.0827
StepF2 - StepF3 -0.012789 0.0165 Inf -0.777 1.0000
StepF2 - StepF4 0.020934 0.0165 Inf 1.271 0.9987
StepF2 - StepF5 0.030238 0.0165 Inf 1.837 0.9338
StepF2 - StepF6 0.017346 0.0165 Inf 1.054 0.9999
StepF2 - StepF7 0.020352 0.0165 Inf 1.236 0.9991
StepF2 - StepF8 0.045709 0.0165 Inf 2.776 0.3280
StepF2 - StepF9 0.042585 0.0165 Inf 2.587 0.4635
StepF2 - StepF10 0.042613 0.0165 Inf 2.588 0.4623
StepF2 - StepF11 0.069579 0.0165 Inf 4.226 0.0032
StepF2 - StepF12 0.106434 0.0165 Inf 6.465 <.0001
StepF2 - StepF13 0.114357 0.0165 Inf 6.946 <.0001
StepF2 - StepF14 0.063478 0.0165 Inf 3.856 0.0139
StepF2 - StepF15 0.075939 0.0165 Inf 4.612 0.0006
StepF2 - StepF16 0.071310 0.0165 Inf 4.331 0.0020
StepF2 - StepF17 0.091388 0.0165 Inf 5.551 <.0001
StepF2 - StepF18 0.091525 0.0165 Inf 5.554 <.0001
StepF3 - StepF4 0.033723 0.0165 Inf 2.048 0.8455
StepF3 - StepF5 0.043027 0.0165 Inf 2.613 0.4433
StepF3 - StepF6 0.030135 0.0165 Inf 1.830 0.9357
StepF3 - StepF7 0.033141 0.0165 Inf 2.013 0.8635
StepF3 - StepF8 0.058498 0.0165 Inf 3.553 0.0405
StepF3 - StepF9 0.055374 0.0165 Inf 3.363 0.0740
StepF3 - StepF10 0.055402 0.0165 Inf 3.365 0.0736
StepF3 - StepF11 0.082368 0.0165 Inf 5.003 0.0001
StepF3 - StepF12 0.119223 0.0165 Inf 7.241 <.0001
StepF3 - StepF13 0.127146 0.0165 Inf 7.723 <.0001
StepF3 - StepF14 0.076267 0.0165 Inf 4.632 0.0005
StepF3 - StepF15 0.088727 0.0165 Inf 5.389 <.0001
StepF3 - StepF16 0.084099 0.0165 Inf 5.108 <.0001
StepF3 - StepF17 0.104177 0.0165 Inf 6.328 <.0001
StepF3 - StepF18 0.104314 0.0165 Inf 6.330 <.0001
StepF4 - StepF5 0.009304 0.0165 Inf 0.565 1.0000
StepF4 - StepF6 -0.003588 0.0165 Inf -0.218 1.0000
StepF4 - StepF7 -0.000582 0.0165 Inf -0.035 1.0000
StepF4 - StepF8 0.024775 0.0165 Inf 1.505 0.9905
StepF4 - StepF9 0.021651 0.0165 Inf 1.315 0.9980
StepF4 - StepF10 0.021679 0.0165 Inf 1.317 0.9979
StepF4 - StepF11 0.048645 0.0165 Inf 2.955 0.2226
StepF4 - StepF12 0.085500 0.0165 Inf 5.193 <.0001
StepF4 - StepF13 0.093424 0.0165 Inf 5.674 <.0001
StepF4 - StepF14 0.042544 0.0165 Inf 2.584 0.4654
StepF4 - StepF15 0.055005 0.0165 Inf 3.341 0.0792
StepF4 - StepF16 0.050376 0.0165 Inf 3.060 0.1724
StepF4 - StepF17 0.070455 0.0165 Inf 4.279 0.0025
StepF4 - StepF18 0.070591 0.0165 Inf 4.284 0.0025
StepF5 - StepF6 -0.012892 0.0165 Inf -0.783 1.0000
StepF5 - StepF7 -0.009885 0.0165 Inf -0.600 1.0000
StepF5 - StepF8 0.015471 0.0165 Inf 0.940 1.0000
StepF5 - StepF9 0.012347 0.0165 Inf 0.750 1.0000
StepF5 - StepF10 0.012375 0.0165 Inf 0.752 1.0000
StepF5 - StepF11 0.039341 0.0165 Inf 2.390 0.6160
StepF5 - StepF12 0.076196 0.0165 Inf 4.628 0.0005
StepF5 - StepF13 0.084120 0.0165 Inf 5.109 <.0001
StepF5 - StepF14 0.033240 0.0165 Inf 2.019 0.8606
StepF5 - StepF15 0.045701 0.0165 Inf 2.776 0.3283
StepF5 - StepF16 0.041072 0.0165 Inf 2.495 0.5343
StepF5 - StepF17 0.061151 0.0165 Inf 3.714 0.0233
StepF5 - StepF18 0.061287 0.0165 Inf 3.719 0.0229
StepF6 - StepF7 0.003006 0.0165 Inf 0.183 1.0000
StepF6 - StepF8 0.028363 0.0165 Inf 1.723 0.9626
StepF6 - StepF9 0.025239 0.0165 Inf 1.533 0.9884
StepF6 - StepF10 0.025267 0.0165 Inf 1.535 0.9882
StepF6 - StepF11 0.052233 0.0165 Inf 3.173 0.1282
StepF6 - StepF12 0.089088 0.0165 Inf 5.411 <.0001
StepF6 - StepF13 0.097011 0.0165 Inf 5.892 <.0001
StepF6 - StepF14 0.046132 0.0165 Inf 2.802 0.3113
StepF6 - StepF15 0.058593 0.0165 Inf 3.559 0.0397
StepF6 - StepF16 0.053964 0.0165 Inf 3.278 0.0954
StepF6 - StepF17 0.074042 0.0165 Inf 4.497 0.0010
StepF6 - StepF18 0.074179 0.0165 Inf 4.501 0.0009
StepF7 - StepF8 0.025357 0.0165 Inf 1.540 0.9878
StepF7 - StepF9 0.022233 0.0165 Inf 1.350 0.9972
StepF7 - StepF10 0.022261 0.0165 Inf 1.352 0.9972
StepF7 - StepF11 0.049227 0.0165 Inf 2.990 0.2047
StepF7 - StepF12 0.086082 0.0165 Inf 5.229 <.0001
StepF7 - StepF13 0.094005 0.0165 Inf 5.710 <.0001
StepF7 - StepF14 0.043126 0.0165 Inf 2.619 0.4388
StepF7 - StepF15 0.055586 0.0165 Inf 3.376 0.0712
StepF7 - StepF16 0.050958 0.0165 Inf 3.095 0.1575
StepF7 - StepF17 0.071036 0.0165 Inf 4.315 0.0022
StepF7 - StepF18 0.071173 0.0165 Inf 4.319 0.0021
StepF8 - StepF9 -0.003124 0.0165 Inf -0.190 1.0000
StepF8 - StepF10 -0.003096 0.0165 Inf -0.188 1.0000
StepF8 - StepF11 0.023870 0.0165 Inf 1.450 0.9937
StepF8 - StepF12 0.060725 0.0165 Inf 3.688 0.0255
StepF8 - StepF13 0.068648 0.0165 Inf 4.170 0.0040
StepF8 - StepF14 0.017769 0.0165 Inf 1.079 0.9998
StepF8 - StepF15 0.030229 0.0165 Inf 1.836 0.9340
StepF8 - StepF16 0.025601 0.0165 Inf 1.555 0.9865
StepF8 - StepF17 0.045679 0.0165 Inf 2.775 0.3292
StepF8 - StepF18 0.045816 0.0165 Inf 2.780 0.3254
StepF9 - StepF10 0.000028 0.0165 Inf 0.002 1.0000
StepF9 - StepF11 0.026994 0.0165 Inf 1.640 0.9768
StepF9 - StepF12 0.063849 0.0165 Inf 3.878 0.0127
StepF9 - StepF13 0.071772 0.0165 Inf 4.359 0.0018
StepF9 - StepF14 0.020893 0.0165 Inf 1.269 0.9987
StepF9 - StepF15 0.033353 0.0165 Inf 2.026 0.8571
StepF9 - StepF16 0.028725 0.0165 Inf 1.745 0.9579
StepF9 - StepF17 0.048803 0.0165 Inf 2.964 0.2176
StepF9 - StepF18 0.048940 0.0165 Inf 2.970 0.2148
StepF10 - StepF11 0.026966 0.0165 Inf 1.638 0.9770
StepF10 - StepF12 0.063821 0.0165 Inf 3.876 0.0128
StepF10 - StepF13 0.071744 0.0165 Inf 4.358 0.0018
StepF10 - StepF14 0.020865 0.0165 Inf 1.267 0.9987
StepF10 - StepF15 0.033325 0.0165 Inf 2.024 0.8580
StepF10 - StepF16 0.028697 0.0165 Inf 1.743 0.9583
StepF10 - StepF17 0.048775 0.0165 Inf 2.963 0.2185
StepF10 - StepF18 0.048912 0.0165 Inf 2.968 0.2157
StepF11 - StepF12 0.036855 0.0165 Inf 2.239 0.7277
StepF11 - StepF13 0.044779 0.0165 Inf 2.720 0.3663
StepF11 - StepF14 -0.006101 0.0165 Inf -0.371 1.0000
StepF11 - StepF15 0.006360 0.0165 Inf 0.386 1.0000
StepF11 - StepF16 0.001731 0.0165 Inf 0.105 1.0000
StepF11 - StepF17 0.021809 0.0165 Inf 1.325 0.9978
StepF11 - StepF18 0.021946 0.0165 Inf 1.332 0.9976
StepF12 - StepF13 0.007924 0.0165 Inf 0.481 1.0000
StepF12 - StepF14 -0.042956 0.0165 Inf -2.609 0.4465
StepF12 - StepF15 -0.030495 0.0165 Inf -1.852 0.9289
StepF12 - StepF16 -0.035124 0.0165 Inf -2.133 0.7968
StepF12 - StepF17 -0.015045 0.0165 Inf -0.914 1.0000
StepF12 - StepF18 -0.014909 0.0165 Inf -0.905 1.0000
StepF13 - StepF14 -0.050880 0.0165 Inf -3.090 0.1594
StepF13 - StepF15 -0.038419 0.0165 Inf -2.334 0.6586
StepF13 - StepF16 -0.043048 0.0165 Inf -2.615 0.4424
StepF13 - StepF17 -0.022969 0.0165 Inf -1.395 0.9959
StepF13 - StepF18 -0.022833 0.0165 Inf -1.386 0.9962
StepF14 - StepF15 0.012461 0.0165 Inf 0.757 1.0000
StepF14 - StepF16 0.007832 0.0165 Inf 0.476 1.0000
StepF14 - StepF17 0.027910 0.0165 Inf 1.695 0.9679
StepF14 - StepF18 0.028047 0.0165 Inf 1.702 0.9666
StepF15 - StepF16 -0.004629 0.0165 Inf -0.281 1.0000
StepF15 - StepF17 0.015450 0.0165 Inf 0.938 1.0000
StepF15 - StepF18 0.015586 0.0165 Inf 0.946 1.0000
StepF16 - StepF17 0.020078 0.0165 Inf 1.220 0.9992
StepF16 - StepF18 0.020215 0.0165 Inf 1.227 0.9991
StepF17 - StepF18 0.000137 0.0165 Inf 0.008 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.036708 0.0165 Inf -2.230 0.7338
StepF1 - StepF3 -0.049497 0.0165 Inf -3.006 0.1967
StepF1 - StepF4 -0.015775 0.0165 Inf -0.958 1.0000
StepF1 - StepF5 -0.006471 0.0165 Inf -0.393 1.0000
StepF1 - StepF6 -0.019362 0.0165 Inf -1.176 0.9995
StepF1 - StepF7 -0.016356 0.0165 Inf -0.993 0.9999
StepF1 - StepF8 0.009001 0.0165 Inf 0.547 1.0000
StepF1 - StepF9 0.005877 0.0165 Inf 0.357 1.0000
StepF1 - StepF10 0.005905 0.0165 Inf 0.359 1.0000
StepF1 - StepF11 0.032871 0.0165 Inf 1.997 0.8715
StepF1 - StepF12 0.069725 0.0165 Inf 4.235 0.0030
StepF1 - StepF13 0.077649 0.0165 Inf 4.716 0.0003
StepF1 - StepF14 0.026770 0.0165 Inf 1.626 0.9786
StepF1 - StepF15 0.039230 0.0165 Inf 2.383 0.6212
StepF1 - StepF16 0.034602 0.0165 Inf 2.102 0.8158
StepF1 - StepF17 0.054680 0.0165 Inf 3.321 0.0840
StepF1 - StepF18 0.054816 0.0165 Inf 3.326 0.0827
StepF2 - StepF3 -0.012789 0.0165 Inf -0.777 1.0000
StepF2 - StepF4 0.020934 0.0165 Inf 1.271 0.9987
StepF2 - StepF5 0.030238 0.0165 Inf 1.837 0.9338
StepF2 - StepF6 0.017346 0.0165 Inf 1.054 0.9999
StepF2 - StepF7 0.020352 0.0165 Inf 1.236 0.9991
StepF2 - StepF8 0.045709 0.0165 Inf 2.776 0.3280
StepF2 - StepF9 0.042585 0.0165 Inf 2.587 0.4635
StepF2 - StepF10 0.042613 0.0165 Inf 2.588 0.4623
StepF2 - StepF11 0.069579 0.0165 Inf 4.226 0.0032
StepF2 - StepF12 0.106434 0.0165 Inf 6.465 <.0001
StepF2 - StepF13 0.114357 0.0165 Inf 6.946 <.0001
StepF2 - StepF14 0.063478 0.0165 Inf 3.856 0.0139
StepF2 - StepF15 0.075939 0.0165 Inf 4.612 0.0006
StepF2 - StepF16 0.071310 0.0165 Inf 4.331 0.0020
StepF2 - StepF17 0.091388 0.0165 Inf 5.551 <.0001
StepF2 - StepF18 0.091525 0.0165 Inf 5.554 <.0001
StepF3 - StepF4 0.033723 0.0165 Inf 2.048 0.8455
StepF3 - StepF5 0.043027 0.0165 Inf 2.613 0.4433
StepF3 - StepF6 0.030135 0.0165 Inf 1.830 0.9357
StepF3 - StepF7 0.033141 0.0165 Inf 2.013 0.8635
StepF3 - StepF8 0.058498 0.0165 Inf 3.553 0.0405
StepF3 - StepF9 0.055374 0.0165 Inf 3.363 0.0740
StepF3 - StepF10 0.055402 0.0165 Inf 3.365 0.0736
StepF3 - StepF11 0.082368 0.0165 Inf 5.003 0.0001
StepF3 - StepF12 0.119223 0.0165 Inf 7.241 <.0001
StepF3 - StepF13 0.127146 0.0165 Inf 7.723 <.0001
StepF3 - StepF14 0.076267 0.0165 Inf 4.632 0.0005
StepF3 - StepF15 0.088727 0.0165 Inf 5.389 <.0001
StepF3 - StepF16 0.084099 0.0165 Inf 5.108 <.0001
StepF3 - StepF17 0.104177 0.0165 Inf 6.328 <.0001
StepF3 - StepF18 0.104314 0.0165 Inf 6.330 <.0001
StepF4 - StepF5 0.009304 0.0165 Inf 0.565 1.0000
StepF4 - StepF6 -0.003588 0.0165 Inf -0.218 1.0000
StepF4 - StepF7 -0.000582 0.0165 Inf -0.035 1.0000
StepF4 - StepF8 0.024775 0.0165 Inf 1.505 0.9905
StepF4 - StepF9 0.021651 0.0165 Inf 1.315 0.9980
StepF4 - StepF10 0.021679 0.0165 Inf 1.317 0.9979
StepF4 - StepF11 0.048645 0.0165 Inf 2.955 0.2226
StepF4 - StepF12 0.085500 0.0165 Inf 5.193 <.0001
StepF4 - StepF13 0.093424 0.0165 Inf 5.674 <.0001
StepF4 - StepF14 0.042544 0.0165 Inf 2.584 0.4654
StepF4 - StepF15 0.055005 0.0165 Inf 3.341 0.0792
StepF4 - StepF16 0.050376 0.0165 Inf 3.060 0.1724
StepF4 - StepF17 0.070455 0.0165 Inf 4.279 0.0025
StepF4 - StepF18 0.070591 0.0165 Inf 4.284 0.0025
StepF5 - StepF6 -0.012892 0.0165 Inf -0.783 1.0000
StepF5 - StepF7 -0.009885 0.0165 Inf -0.600 1.0000
StepF5 - StepF8 0.015471 0.0165 Inf 0.940 1.0000
StepF5 - StepF9 0.012347 0.0165 Inf 0.750 1.0000
StepF5 - StepF10 0.012375 0.0165 Inf 0.752 1.0000
StepF5 - StepF11 0.039341 0.0165 Inf 2.390 0.6160
StepF5 - StepF12 0.076196 0.0165 Inf 4.628 0.0005
StepF5 - StepF13 0.084120 0.0165 Inf 5.109 <.0001
StepF5 - StepF14 0.033240 0.0165 Inf 2.019 0.8606
StepF5 - StepF15 0.045701 0.0165 Inf 2.776 0.3283
StepF5 - StepF16 0.041072 0.0165 Inf 2.495 0.5343
StepF5 - StepF17 0.061151 0.0165 Inf 3.714 0.0233
StepF5 - StepF18 0.061287 0.0165 Inf 3.719 0.0229
StepF6 - StepF7 0.003006 0.0165 Inf 0.183 1.0000
StepF6 - StepF8 0.028363 0.0165 Inf 1.723 0.9626
StepF6 - StepF9 0.025239 0.0165 Inf 1.533 0.9884
StepF6 - StepF10 0.025267 0.0165 Inf 1.535 0.9882
StepF6 - StepF11 0.052233 0.0165 Inf 3.173 0.1282
StepF6 - StepF12 0.089088 0.0165 Inf 5.411 <.0001
StepF6 - StepF13 0.097011 0.0165 Inf 5.892 <.0001
StepF6 - StepF14 0.046132 0.0165 Inf 2.802 0.3113
StepF6 - StepF15 0.058593 0.0165 Inf 3.559 0.0397
StepF6 - StepF16 0.053964 0.0165 Inf 3.278 0.0954
StepF6 - StepF17 0.074042 0.0165 Inf 4.497 0.0010
StepF6 - StepF18 0.074179 0.0165 Inf 4.501 0.0009
StepF7 - StepF8 0.025357 0.0165 Inf 1.540 0.9878
StepF7 - StepF9 0.022233 0.0165 Inf 1.350 0.9972
StepF7 - StepF10 0.022261 0.0165 Inf 1.352 0.9972
StepF7 - StepF11 0.049227 0.0165 Inf 2.990 0.2047
StepF7 - StepF12 0.086082 0.0165 Inf 5.229 <.0001
StepF7 - StepF13 0.094005 0.0165 Inf 5.710 <.0001
StepF7 - StepF14 0.043126 0.0165 Inf 2.619 0.4388
StepF7 - StepF15 0.055586 0.0165 Inf 3.376 0.0712
StepF7 - StepF16 0.050958 0.0165 Inf 3.095 0.1575
StepF7 - StepF17 0.071036 0.0165 Inf 4.315 0.0022
StepF7 - StepF18 0.071173 0.0165 Inf 4.319 0.0021
StepF8 - StepF9 -0.003124 0.0165 Inf -0.190 1.0000
StepF8 - StepF10 -0.003096 0.0165 Inf -0.188 1.0000
StepF8 - StepF11 0.023870 0.0165 Inf 1.450 0.9937
StepF8 - StepF12 0.060725 0.0165 Inf 3.688 0.0255
StepF8 - StepF13 0.068648 0.0165 Inf 4.170 0.0040
StepF8 - StepF14 0.017769 0.0165 Inf 1.079 0.9998
StepF8 - StepF15 0.030229 0.0165 Inf 1.836 0.9340
StepF8 - StepF16 0.025601 0.0165 Inf 1.555 0.9865
StepF8 - StepF17 0.045679 0.0165 Inf 2.775 0.3292
StepF8 - StepF18 0.045816 0.0165 Inf 2.780 0.3254
StepF9 - StepF10 0.000028 0.0165 Inf 0.002 1.0000
StepF9 - StepF11 0.026994 0.0165 Inf 1.640 0.9768
StepF9 - StepF12 0.063849 0.0165 Inf 3.878 0.0127
StepF9 - StepF13 0.071772 0.0165 Inf 4.359 0.0018
StepF9 - StepF14 0.020893 0.0165 Inf 1.269 0.9987
StepF9 - StepF15 0.033353 0.0165 Inf 2.026 0.8571
StepF9 - StepF16 0.028725 0.0165 Inf 1.745 0.9579
StepF9 - StepF17 0.048803 0.0165 Inf 2.964 0.2176
StepF9 - StepF18 0.048940 0.0165 Inf 2.970 0.2148
StepF10 - StepF11 0.026966 0.0165 Inf 1.638 0.9770
StepF10 - StepF12 0.063821 0.0165 Inf 3.876 0.0128
StepF10 - StepF13 0.071744 0.0165 Inf 4.358 0.0018
StepF10 - StepF14 0.020865 0.0165 Inf 1.267 0.9987
StepF10 - StepF15 0.033325 0.0165 Inf 2.024 0.8580
StepF10 - StepF16 0.028697 0.0165 Inf 1.743 0.9583
StepF10 - StepF17 0.048775 0.0165 Inf 2.963 0.2185
StepF10 - StepF18 0.048912 0.0165 Inf 2.968 0.2157
StepF11 - StepF12 0.036855 0.0165 Inf 2.239 0.7277
StepF11 - StepF13 0.044779 0.0165 Inf 2.720 0.3663
StepF11 - StepF14 -0.006101 0.0165 Inf -0.371 1.0000
StepF11 - StepF15 0.006360 0.0165 Inf 0.386 1.0000
StepF11 - StepF16 0.001731 0.0165 Inf 0.105 1.0000
StepF11 - StepF17 0.021809 0.0165 Inf 1.325 0.9978
StepF11 - StepF18 0.021946 0.0165 Inf 1.332 0.9976
StepF12 - StepF13 0.007924 0.0165 Inf 0.481 1.0000
StepF12 - StepF14 -0.042956 0.0165 Inf -2.609 0.4465
StepF12 - StepF15 -0.030495 0.0165 Inf -1.852 0.9289
StepF12 - StepF16 -0.035124 0.0165 Inf -2.133 0.7968
StepF12 - StepF17 -0.015045 0.0165 Inf -0.914 1.0000
StepF12 - StepF18 -0.014909 0.0165 Inf -0.905 1.0000
StepF13 - StepF14 -0.050880 0.0165 Inf -3.090 0.1594
StepF13 - StepF15 -0.038419 0.0165 Inf -2.334 0.6586
StepF13 - StepF16 -0.043048 0.0165 Inf -2.615 0.4424
StepF13 - StepF17 -0.022969 0.0165 Inf -1.395 0.9959
StepF13 - StepF18 -0.022833 0.0165 Inf -1.386 0.9962
StepF14 - StepF15 0.012461 0.0165 Inf 0.757 1.0000
StepF14 - StepF16 0.007832 0.0165 Inf 0.476 1.0000
StepF14 - StepF17 0.027910 0.0165 Inf 1.695 0.9679
StepF14 - StepF18 0.028047 0.0165 Inf 1.702 0.9666
StepF15 - StepF16 -0.004629 0.0165 Inf -0.281 1.0000
StepF15 - StepF17 0.015450 0.0165 Inf 0.938 1.0000
StepF15 - StepF18 0.015586 0.0165 Inf 0.946 1.0000
StepF16 - StepF17 0.020078 0.0165 Inf 1.220 0.9992
StepF16 - StepF18 0.020215 0.0165 Inf 1.227 0.9991
StepF17 - StepF18 0.000137 0.0165 Inf 0.008 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.036708 0.0165 Inf 2.230 0.4030
StepF3 - StepF2 0.012789 0.0165 Inf 0.777 1.0000
StepF4 - StepF3 -0.033723 0.0165 Inf -2.048 0.5675
StepF5 - StepF4 -0.009304 0.0165 Inf -0.565 1.0000
StepF6 - StepF5 0.012892 0.0165 Inf 0.783 1.0000
StepF7 - StepF6 -0.003006 0.0165 Inf -0.183 1.0000
StepF8 - StepF7 -0.025357 0.0165 Inf -1.540 1.0000
StepF9 - StepF8 0.003124 0.0165 Inf 0.190 1.0000
StepF10 - StepF9 -0.000028 0.0165 Inf -0.002 1.0000
StepF11 - StepF10 -0.026966 0.0165 Inf -1.638 1.0000
StepF12 - StepF11 -0.036855 0.0165 Inf -2.239 0.4030
StepF13 - StepF12 -0.007924 0.0165 Inf -0.481 1.0000
StepF14 - StepF13 0.050880 0.0165 Inf 3.090 0.0340
StepF15 - StepF14 -0.012461 0.0165 Inf -0.757 1.0000
StepF16 - StepF15 0.004629 0.0165 Inf 0.281 1.0000
StepF17 - StepF16 -0.020078 0.0165 Inf -1.220 1.0000
StepF18 - StepF17 -0.000137 0.0165 Inf -0.008 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.036708 0.0165 Inf 2.230 0.4030
StepF3 - StepF2 0.012789 0.0165 Inf 0.777 1.0000
StepF4 - StepF3 -0.033723 0.0165 Inf -2.048 0.5675
StepF5 - StepF4 -0.009304 0.0165 Inf -0.565 1.0000
StepF6 - StepF5 0.012892 0.0165 Inf 0.783 1.0000
StepF7 - StepF6 -0.003006 0.0165 Inf -0.183 1.0000
StepF8 - StepF7 -0.025357 0.0165 Inf -1.540 1.0000
StepF9 - StepF8 0.003124 0.0165 Inf 0.190 1.0000
StepF10 - StepF9 -0.000028 0.0165 Inf -0.002 1.0000
StepF11 - StepF10 -0.026966 0.0165 Inf -1.638 1.0000
StepF12 - StepF11 -0.036855 0.0165 Inf -2.239 0.4030
StepF13 - StepF12 -0.007924 0.0165 Inf -0.481 1.0000
StepF14 - StepF13 0.050880 0.0165 Inf 3.090 0.0340
StepF15 - StepF14 -0.012461 0.0165 Inf -0.757 1.0000
StepF16 - StepF15 0.004629 0.0165 Inf 0.281 1.0000
StepF17 - StepF16 -0.020078 0.0165 Inf -1.220 1.0000
StepF18 - StepF17 -0.000137 0.0165 Inf -0.008 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests
==============================
TRAINING | Block 3 (18 steps) | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 262.1257 17 <2e-16 ***
Accuracy 0.1535 1 0.6952
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.587 0.0520 Inf 0.485 0.689
2 0.677 0.0520 Inf 0.576 0.779
3 0.695 0.0520 Inf 0.593 0.797
4 0.589 0.0520 Inf 0.487 0.691
5 0.597 0.0520 Inf 0.495 0.699
6 0.626 0.0520 Inf 0.524 0.728
7 0.647 0.0520 Inf 0.545 0.749
8 0.572 0.0520 Inf 0.470 0.674
9 0.591 0.0520 Inf 0.489 0.693
10 0.640 0.0520 Inf 0.538 0.741
11 0.643 0.0520 Inf 0.541 0.745
12 0.531 0.0520 Inf 0.429 0.633
13 0.543 0.0520 Inf 0.441 0.644
14 0.556 0.0520 Inf 0.454 0.658
15 0.589 0.0520 Inf 0.487 0.691
16 0.554 0.0520 Inf 0.452 0.656
17 0.558 0.0520 Inf 0.456 0.660
18 0.532 0.0520 Inf 0.431 0.634
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.584 0.0519 Inf 0.482 0.686
2 0.674 0.0519 Inf 0.572 0.776
3 0.692 0.0519 Inf 0.590 0.794
4 0.586 0.0519 Inf 0.484 0.687
5 0.594 0.0519 Inf 0.492 0.695
6 0.623 0.0519 Inf 0.521 0.724
7 0.644 0.0519 Inf 0.542 0.746
8 0.569 0.0519 Inf 0.467 0.671
9 0.588 0.0519 Inf 0.486 0.690
10 0.636 0.0519 Inf 0.534 0.738
11 0.639 0.0519 Inf 0.538 0.741
12 0.528 0.0519 Inf 0.426 0.629
13 0.539 0.0519 Inf 0.437 0.641
14 0.553 0.0519 Inf 0.451 0.654
15 0.586 0.0519 Inf 0.484 0.687
16 0.550 0.0519 Inf 0.449 0.652
17 0.555 0.0519 Inf 0.453 0.657
18 0.529 0.0519 Inf 0.427 0.631
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -9.02e-02 0.0176 Inf -5.110 <.0001
StepF1 - StepF3 -1.08e-01 0.0176 Inf -6.128 <.0001
StepF1 - StepF4 -1.71e-03 0.0176 Inf -0.097 1.0000
StepF1 - StepF5 -9.67e-03 0.0176 Inf -0.548 1.0000
StepF1 - StepF6 -3.88e-02 0.0176 Inf -2.198 0.7556
StepF1 - StepF7 -6.00e-02 0.0176 Inf -3.402 0.0658
StepF1 - StepF8 1.51e-02 0.0176 Inf 0.853 1.0000
StepF1 - StepF9 -3.90e-03 0.0176 Inf -0.221 1.0000
StepF1 - StepF10 -5.24e-02 0.0176 Inf -2.968 0.2156
StepF1 - StepF11 -5.56e-02 0.0176 Inf -3.150 0.1362
StepF1 - StepF12 5.62e-02 0.0176 Inf 3.187 0.1232
StepF1 - StepF13 4.47e-02 0.0176 Inf 2.531 0.5061
StepF1 - StepF14 3.13e-02 0.0176 Inf 1.775 0.9509
StepF1 - StepF15 -1.69e-03 0.0176 Inf -0.096 1.0000
StepF1 - StepF16 3.35e-02 0.0176 Inf 1.899 0.9128
StepF1 - StepF17 2.89e-02 0.0176 Inf 1.639 0.9768
StepF1 - StepF18 5.48e-02 0.0177 Inf 3.101 0.1552
StepF2 - StepF3 -1.80e-02 0.0176 Inf -1.018 0.9999
StepF2 - StepF4 8.85e-02 0.0176 Inf 5.013 0.0001
StepF2 - StepF5 8.05e-02 0.0176 Inf 4.562 0.0007
StepF2 - StepF6 5.14e-02 0.0176 Inf 2.913 0.2452
StepF2 - StepF7 3.01e-02 0.0176 Inf 1.708 0.9654
StepF2 - StepF8 1.05e-01 0.0176 Inf 5.963 <.0001
StepF2 - StepF9 8.63e-02 0.0176 Inf 4.889 0.0001
StepF2 - StepF10 3.78e-02 0.0176 Inf 2.142 0.7915
StepF2 - StepF11 3.46e-02 0.0176 Inf 1.960 0.8882
StepF2 - StepF12 1.46e-01 0.0176 Inf 8.297 <.0001
StepF2 - StepF13 1.35e-01 0.0176 Inf 7.641 <.0001
StepF2 - StepF14 1.21e-01 0.0176 Inf 6.885 <.0001
StepF2 - StepF15 8.85e-02 0.0176 Inf 5.014 0.0001
StepF2 - StepF16 1.24e-01 0.0176 Inf 7.009 <.0001
StepF2 - StepF17 1.19e-01 0.0176 Inf 6.749 <.0001
StepF2 - StepF18 1.45e-01 0.0177 Inf 8.206 <.0001
StepF3 - StepF4 1.06e-01 0.0176 Inf 6.031 <.0001
StepF3 - StepF5 9.85e-02 0.0176 Inf 5.580 <.0001
StepF3 - StepF6 6.94e-02 0.0176 Inf 3.931 0.0104
StepF3 - StepF7 4.81e-02 0.0176 Inf 2.726 0.3617
StepF3 - StepF8 1.23e-01 0.0176 Inf 6.981 <.0001
StepF3 - StepF9 1.04e-01 0.0176 Inf 5.907 <.0001
StepF3 - StepF10 5.58e-02 0.0176 Inf 3.160 0.1327
StepF3 - StepF11 5.25e-02 0.0176 Inf 2.978 0.2107
StepF3 - StepF12 1.64e-01 0.0176 Inf 9.315 <.0001
StepF3 - StepF13 1.53e-01 0.0176 Inf 8.659 <.0001
StepF3 - StepF14 1.39e-01 0.0176 Inf 7.903 <.0001
StepF3 - StepF15 1.06e-01 0.0176 Inf 6.032 <.0001
StepF3 - StepF16 1.42e-01 0.0176 Inf 8.027 <.0001
StepF3 - StepF17 1.37e-01 0.0176 Inf 7.767 <.0001
StepF3 - StepF18 1.63e-01 0.0177 Inf 9.223 <.0001
StepF4 - StepF5 -7.96e-03 0.0176 Inf -0.451 1.0000
StepF4 - StepF6 -3.71e-02 0.0176 Inf -2.101 0.8164
StepF4 - StepF7 -5.83e-02 0.0176 Inf -3.305 0.0882
StepF4 - StepF8 1.68e-02 0.0176 Inf 0.950 1.0000
StepF4 - StepF9 -2.19e-03 0.0176 Inf -0.124 1.0000
StepF4 - StepF10 -5.07e-02 0.0176 Inf -2.871 0.2688
StepF4 - StepF11 -5.39e-02 0.0176 Inf -3.053 0.1752
StepF4 - StepF12 5.79e-02 0.0176 Inf 3.284 0.0937
StepF4 - StepF13 4.64e-02 0.0176 Inf 2.628 0.4323
StepF4 - StepF14 3.30e-02 0.0176 Inf 1.872 0.9223
StepF4 - StepF15 2.13e-05 0.0176 Inf 0.001 1.0000
StepF4 - StepF16 3.52e-02 0.0176 Inf 1.996 0.8718
StepF4 - StepF17 3.06e-02 0.0176 Inf 1.736 0.9598
StepF4 - StepF18 5.65e-02 0.0177 Inf 3.198 0.1197
StepF5 - StepF6 -2.91e-02 0.0176 Inf -1.650 0.9753
StepF5 - StepF7 -5.04e-02 0.0176 Inf -2.854 0.2792
StepF5 - StepF8 2.47e-02 0.0176 Inf 1.401 0.9957
StepF5 - StepF9 5.76e-03 0.0176 Inf 0.327 1.0000
StepF5 - StepF10 -4.27e-02 0.0176 Inf -2.420 0.5922
StepF5 - StepF11 -4.59e-02 0.0176 Inf -2.602 0.4516
StepF5 - StepF12 6.59e-02 0.0176 Inf 3.735 0.0216
StepF5 - StepF13 5.43e-02 0.0176 Inf 3.079 0.1641
StepF5 - StepF14 4.10e-02 0.0176 Inf 2.323 0.6665
StepF5 - StepF15 7.98e-03 0.0176 Inf 0.452 1.0000
StepF5 - StepF16 4.32e-02 0.0176 Inf 2.447 0.5716
StepF5 - StepF17 3.86e-02 0.0176 Inf 2.187 0.7626
StepF5 - StepF18 6.44e-02 0.0177 Inf 3.648 0.0293
StepF6 - StepF7 -2.12e-02 0.0176 Inf -1.204 0.9993
StepF6 - StepF8 5.38e-02 0.0176 Inf 3.051 0.1763
StepF6 - StepF9 3.49e-02 0.0176 Inf 1.976 0.8808
StepF6 - StepF10 -1.36e-02 0.0176 Inf -0.771 1.0000
StepF6 - StepF11 -1.68e-02 0.0176 Inf -0.953 1.0000
StepF6 - StepF12 9.50e-02 0.0176 Inf 5.385 <.0001
StepF6 - StepF13 8.34e-02 0.0176 Inf 4.729 0.0003
StepF6 - StepF14 7.01e-02 0.0176 Inf 3.973 0.0089
StepF6 - StepF15 3.71e-02 0.0176 Inf 2.102 0.8157
StepF6 - StepF16 7.23e-02 0.0176 Inf 4.097 0.0054
StepF6 - StepF17 6.77e-02 0.0176 Inf 3.837 0.0149
StepF6 - StepF18 9.35e-02 0.0177 Inf 5.296 <.0001
StepF7 - StepF8 7.51e-02 0.0176 Inf 4.255 0.0028
StepF7 - StepF9 5.61e-02 0.0176 Inf 3.181 0.1255
StepF7 - StepF10 7.65e-03 0.0176 Inf 0.433 1.0000
StepF7 - StepF11 4.44e-03 0.0176 Inf 0.251 1.0000
StepF7 - StepF12 1.16e-01 0.0176 Inf 6.589 <.0001
StepF7 - StepF13 1.05e-01 0.0176 Inf 5.933 <.0001
StepF7 - StepF14 9.13e-02 0.0176 Inf 5.177 <.0001
StepF7 - StepF15 5.83e-02 0.0176 Inf 3.306 0.0879
StepF7 - StepF16 9.35e-02 0.0176 Inf 5.301 <.0001
StepF7 - StepF17 8.89e-02 0.0176 Inf 5.041 0.0001
StepF7 - StepF18 1.15e-01 0.0177 Inf 6.499 <.0001
StepF8 - StepF9 -1.90e-02 0.0176 Inf -1.074 0.9999
StepF8 - StepF10 -6.74e-02 0.0176 Inf -3.821 0.0158
StepF8 - StepF11 -7.06e-02 0.0176 Inf -4.003 0.0078
StepF8 - StepF12 4.12e-02 0.0176 Inf 2.334 0.6583
StepF8 - StepF13 2.96e-02 0.0176 Inf 1.678 0.9709
StepF8 - StepF14 1.63e-02 0.0176 Inf 0.922 1.0000
StepF8 - StepF15 -1.67e-02 0.0176 Inf -0.949 1.0000
StepF8 - StepF16 1.85e-02 0.0176 Inf 1.046 0.9999
StepF8 - StepF17 1.39e-02 0.0176 Inf 0.786 1.0000
StepF8 - StepF18 3.97e-02 0.0177 Inf 2.248 0.7208
StepF9 - StepF10 -4.85e-02 0.0176 Inf -2.747 0.3476
StepF9 - StepF11 -5.17e-02 0.0176 Inf -2.929 0.2362
StepF9 - StepF12 6.01e-02 0.0176 Inf 3.408 0.0645
StepF9 - StepF13 4.86e-02 0.0176 Inf 2.752 0.3440
StepF9 - StepF14 3.52e-02 0.0176 Inf 1.996 0.8716
StepF9 - StepF15 2.21e-03 0.0176 Inf 0.125 1.0000
StepF9 - StepF16 3.74e-02 0.0176 Inf 2.120 0.8049
StepF9 - StepF17 3.28e-02 0.0176 Inf 1.860 0.9262
StepF9 - StepF18 5.87e-02 0.0177 Inf 3.322 0.0839
StepF10 - StepF11 -3.21e-03 0.0176 Inf -0.182 1.0000
StepF10 - StepF12 1.09e-01 0.0176 Inf 6.155 <.0001
StepF10 - StepF13 9.70e-02 0.0176 Inf 5.499 <.0001
StepF10 - StepF14 8.37e-02 0.0176 Inf 4.743 0.0003
StepF10 - StepF15 5.07e-02 0.0176 Inf 2.872 0.2681
StepF10 - StepF16 8.59e-02 0.0176 Inf 4.867 0.0002
StepF10 - StepF17 8.13e-02 0.0176 Inf 4.607 0.0006
StepF10 - StepF18 1.07e-01 0.0177 Inf 6.066 <.0001
StepF11 - StepF12 1.12e-01 0.0176 Inf 6.337 <.0001
StepF11 - StepF13 1.00e-01 0.0176 Inf 5.681 <.0001
StepF11 - StepF14 8.69e-02 0.0176 Inf 4.925 0.0001
StepF11 - StepF15 5.39e-02 0.0176 Inf 3.054 0.1747
StepF11 - StepF16 8.91e-02 0.0176 Inf 5.049 0.0001
StepF11 - StepF17 8.45e-02 0.0176 Inf 4.789 0.0002
StepF11 - StepF18 1.10e-01 0.0177 Inf 6.248 <.0001
StepF12 - StepF13 -1.16e-02 0.0176 Inf -0.656 1.0000
StepF12 - StepF14 -2.49e-02 0.0176 Inf -1.412 0.9953
StepF12 - StepF15 -5.79e-02 0.0176 Inf -3.283 0.0940
StepF12 - StepF16 -2.27e-02 0.0176 Inf -1.288 0.9984
StepF12 - StepF17 -2.73e-02 0.0176 Inf -1.548 0.9871
StepF12 - StepF18 -1.47e-03 0.0177 Inf -0.083 1.0000
StepF13 - StepF14 -1.33e-02 0.0176 Inf -0.756 1.0000
StepF13 - StepF15 -4.64e-02 0.0176 Inf -2.627 0.4332
StepF13 - StepF16 -1.12e-02 0.0176 Inf -0.632 1.0000
StepF13 - StepF17 -1.57e-02 0.0176 Inf -0.892 1.0000
StepF13 - StepF18 1.01e-02 0.0177 Inf 0.572 1.0000
StepF14 - StepF15 -3.30e-02 0.0176 Inf -1.871 0.9227
StepF14 - StepF16 2.19e-03 0.0176 Inf 0.124 1.0000
StepF14 - StepF17 -2.40e-03 0.0176 Inf -0.136 1.0000
StepF14 - StepF18 2.34e-02 0.0177 Inf 1.327 0.9977
StepF15 - StepF16 3.52e-02 0.0176 Inf 1.995 0.8724
StepF15 - StepF17 3.06e-02 0.0176 Inf 1.735 0.9601
StepF15 - StepF18 5.65e-02 0.0177 Inf 3.196 0.1201
StepF16 - StepF17 -4.58e-03 0.0176 Inf -0.260 1.0000
StepF16 - StepF18 2.13e-02 0.0177 Inf 1.204 0.9993
StepF17 - StepF18 2.58e-02 0.0177 Inf 1.463 0.9930
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -9.02e-02 0.0176 Inf -5.110 <.0001
StepF1 - StepF3 -1.08e-01 0.0176 Inf -6.128 <.0001
StepF1 - StepF4 -1.71e-03 0.0176 Inf -0.097 1.0000
StepF1 - StepF5 -9.67e-03 0.0176 Inf -0.548 1.0000
StepF1 - StepF6 -3.88e-02 0.0176 Inf -2.198 0.7556
StepF1 - StepF7 -6.00e-02 0.0176 Inf -3.402 0.0658
StepF1 - StepF8 1.51e-02 0.0176 Inf 0.853 1.0000
StepF1 - StepF9 -3.90e-03 0.0176 Inf -0.221 1.0000
StepF1 - StepF10 -5.24e-02 0.0176 Inf -2.968 0.2156
StepF1 - StepF11 -5.56e-02 0.0176 Inf -3.150 0.1362
StepF1 - StepF12 5.62e-02 0.0176 Inf 3.187 0.1232
StepF1 - StepF13 4.47e-02 0.0176 Inf 2.531 0.5061
StepF1 - StepF14 3.13e-02 0.0176 Inf 1.775 0.9509
StepF1 - StepF15 -1.69e-03 0.0176 Inf -0.096 1.0000
StepF1 - StepF16 3.35e-02 0.0176 Inf 1.899 0.9128
StepF1 - StepF17 2.89e-02 0.0176 Inf 1.639 0.9768
StepF1 - StepF18 5.48e-02 0.0177 Inf 3.101 0.1552
StepF2 - StepF3 -1.80e-02 0.0176 Inf -1.018 0.9999
StepF2 - StepF4 8.85e-02 0.0176 Inf 5.013 0.0001
StepF2 - StepF5 8.05e-02 0.0176 Inf 4.562 0.0007
StepF2 - StepF6 5.14e-02 0.0176 Inf 2.913 0.2452
StepF2 - StepF7 3.01e-02 0.0176 Inf 1.708 0.9654
StepF2 - StepF8 1.05e-01 0.0176 Inf 5.963 <.0001
StepF2 - StepF9 8.63e-02 0.0176 Inf 4.889 0.0001
StepF2 - StepF10 3.78e-02 0.0176 Inf 2.142 0.7915
StepF2 - StepF11 3.46e-02 0.0176 Inf 1.960 0.8882
StepF2 - StepF12 1.46e-01 0.0176 Inf 8.297 <.0001
StepF2 - StepF13 1.35e-01 0.0176 Inf 7.641 <.0001
StepF2 - StepF14 1.21e-01 0.0176 Inf 6.885 <.0001
StepF2 - StepF15 8.85e-02 0.0176 Inf 5.014 0.0001
StepF2 - StepF16 1.24e-01 0.0176 Inf 7.009 <.0001
StepF2 - StepF17 1.19e-01 0.0176 Inf 6.749 <.0001
StepF2 - StepF18 1.45e-01 0.0177 Inf 8.206 <.0001
StepF3 - StepF4 1.06e-01 0.0176 Inf 6.031 <.0001
StepF3 - StepF5 9.85e-02 0.0176 Inf 5.580 <.0001
StepF3 - StepF6 6.94e-02 0.0176 Inf 3.931 0.0104
StepF3 - StepF7 4.81e-02 0.0176 Inf 2.726 0.3617
StepF3 - StepF8 1.23e-01 0.0176 Inf 6.981 <.0001
StepF3 - StepF9 1.04e-01 0.0176 Inf 5.907 <.0001
StepF3 - StepF10 5.58e-02 0.0176 Inf 3.160 0.1327
StepF3 - StepF11 5.25e-02 0.0176 Inf 2.978 0.2107
StepF3 - StepF12 1.64e-01 0.0176 Inf 9.315 <.0001
StepF3 - StepF13 1.53e-01 0.0176 Inf 8.659 <.0001
StepF3 - StepF14 1.39e-01 0.0176 Inf 7.903 <.0001
StepF3 - StepF15 1.06e-01 0.0176 Inf 6.032 <.0001
StepF3 - StepF16 1.42e-01 0.0176 Inf 8.027 <.0001
StepF3 - StepF17 1.37e-01 0.0176 Inf 7.767 <.0001
StepF3 - StepF18 1.63e-01 0.0177 Inf 9.223 <.0001
StepF4 - StepF5 -7.96e-03 0.0176 Inf -0.451 1.0000
StepF4 - StepF6 -3.71e-02 0.0176 Inf -2.101 0.8164
StepF4 - StepF7 -5.83e-02 0.0176 Inf -3.305 0.0882
StepF4 - StepF8 1.68e-02 0.0176 Inf 0.950 1.0000
StepF4 - StepF9 -2.19e-03 0.0176 Inf -0.124 1.0000
StepF4 - StepF10 -5.07e-02 0.0176 Inf -2.871 0.2688
StepF4 - StepF11 -5.39e-02 0.0176 Inf -3.053 0.1752
StepF4 - StepF12 5.79e-02 0.0176 Inf 3.284 0.0937
StepF4 - StepF13 4.64e-02 0.0176 Inf 2.628 0.4323
StepF4 - StepF14 3.30e-02 0.0176 Inf 1.872 0.9223
StepF4 - StepF15 2.13e-05 0.0176 Inf 0.001 1.0000
StepF4 - StepF16 3.52e-02 0.0176 Inf 1.996 0.8718
StepF4 - StepF17 3.06e-02 0.0176 Inf 1.736 0.9598
StepF4 - StepF18 5.65e-02 0.0177 Inf 3.198 0.1197
StepF5 - StepF6 -2.91e-02 0.0176 Inf -1.650 0.9753
StepF5 - StepF7 -5.04e-02 0.0176 Inf -2.854 0.2792
StepF5 - StepF8 2.47e-02 0.0176 Inf 1.401 0.9957
StepF5 - StepF9 5.76e-03 0.0176 Inf 0.327 1.0000
StepF5 - StepF10 -4.27e-02 0.0176 Inf -2.420 0.5922
StepF5 - StepF11 -4.59e-02 0.0176 Inf -2.602 0.4516
StepF5 - StepF12 6.59e-02 0.0176 Inf 3.735 0.0216
StepF5 - StepF13 5.43e-02 0.0176 Inf 3.079 0.1641
StepF5 - StepF14 4.10e-02 0.0176 Inf 2.323 0.6665
StepF5 - StepF15 7.98e-03 0.0176 Inf 0.452 1.0000
StepF5 - StepF16 4.32e-02 0.0176 Inf 2.447 0.5716
StepF5 - StepF17 3.86e-02 0.0176 Inf 2.187 0.7626
StepF5 - StepF18 6.44e-02 0.0177 Inf 3.648 0.0293
StepF6 - StepF7 -2.12e-02 0.0176 Inf -1.204 0.9993
StepF6 - StepF8 5.38e-02 0.0176 Inf 3.051 0.1763
StepF6 - StepF9 3.49e-02 0.0176 Inf 1.976 0.8808
StepF6 - StepF10 -1.36e-02 0.0176 Inf -0.771 1.0000
StepF6 - StepF11 -1.68e-02 0.0176 Inf -0.953 1.0000
StepF6 - StepF12 9.50e-02 0.0176 Inf 5.385 <.0001
StepF6 - StepF13 8.34e-02 0.0176 Inf 4.729 0.0003
StepF6 - StepF14 7.01e-02 0.0176 Inf 3.973 0.0089
StepF6 - StepF15 3.71e-02 0.0176 Inf 2.102 0.8157
StepF6 - StepF16 7.23e-02 0.0176 Inf 4.097 0.0054
StepF6 - StepF17 6.77e-02 0.0176 Inf 3.837 0.0149
StepF6 - StepF18 9.35e-02 0.0177 Inf 5.296 <.0001
StepF7 - StepF8 7.51e-02 0.0176 Inf 4.255 0.0028
StepF7 - StepF9 5.61e-02 0.0176 Inf 3.181 0.1255
StepF7 - StepF10 7.65e-03 0.0176 Inf 0.433 1.0000
StepF7 - StepF11 4.44e-03 0.0176 Inf 0.251 1.0000
StepF7 - StepF12 1.16e-01 0.0176 Inf 6.589 <.0001
StepF7 - StepF13 1.05e-01 0.0176 Inf 5.933 <.0001
StepF7 - StepF14 9.13e-02 0.0176 Inf 5.177 <.0001
StepF7 - StepF15 5.83e-02 0.0176 Inf 3.306 0.0879
StepF7 - StepF16 9.35e-02 0.0176 Inf 5.301 <.0001
StepF7 - StepF17 8.89e-02 0.0176 Inf 5.041 0.0001
StepF7 - StepF18 1.15e-01 0.0177 Inf 6.499 <.0001
StepF8 - StepF9 -1.90e-02 0.0176 Inf -1.074 0.9999
StepF8 - StepF10 -6.74e-02 0.0176 Inf -3.821 0.0158
StepF8 - StepF11 -7.06e-02 0.0176 Inf -4.003 0.0078
StepF8 - StepF12 4.12e-02 0.0176 Inf 2.334 0.6583
StepF8 - StepF13 2.96e-02 0.0176 Inf 1.678 0.9709
StepF8 - StepF14 1.63e-02 0.0176 Inf 0.922 1.0000
StepF8 - StepF15 -1.67e-02 0.0176 Inf -0.949 1.0000
StepF8 - StepF16 1.85e-02 0.0176 Inf 1.046 0.9999
StepF8 - StepF17 1.39e-02 0.0176 Inf 0.786 1.0000
StepF8 - StepF18 3.97e-02 0.0177 Inf 2.248 0.7208
StepF9 - StepF10 -4.85e-02 0.0176 Inf -2.747 0.3476
StepF9 - StepF11 -5.17e-02 0.0176 Inf -2.929 0.2362
StepF9 - StepF12 6.01e-02 0.0176 Inf 3.408 0.0645
StepF9 - StepF13 4.86e-02 0.0176 Inf 2.752 0.3440
StepF9 - StepF14 3.52e-02 0.0176 Inf 1.996 0.8716
StepF9 - StepF15 2.21e-03 0.0176 Inf 0.125 1.0000
StepF9 - StepF16 3.74e-02 0.0176 Inf 2.120 0.8049
StepF9 - StepF17 3.28e-02 0.0176 Inf 1.860 0.9262
StepF9 - StepF18 5.87e-02 0.0177 Inf 3.322 0.0839
StepF10 - StepF11 -3.21e-03 0.0176 Inf -0.182 1.0000
StepF10 - StepF12 1.09e-01 0.0176 Inf 6.155 <.0001
StepF10 - StepF13 9.70e-02 0.0176 Inf 5.499 <.0001
StepF10 - StepF14 8.37e-02 0.0176 Inf 4.743 0.0003
StepF10 - StepF15 5.07e-02 0.0176 Inf 2.872 0.2681
StepF10 - StepF16 8.59e-02 0.0176 Inf 4.867 0.0002
StepF10 - StepF17 8.13e-02 0.0176 Inf 4.607 0.0006
StepF10 - StepF18 1.07e-01 0.0177 Inf 6.066 <.0001
StepF11 - StepF12 1.12e-01 0.0176 Inf 6.337 <.0001
StepF11 - StepF13 1.00e-01 0.0176 Inf 5.681 <.0001
StepF11 - StepF14 8.69e-02 0.0176 Inf 4.925 0.0001
StepF11 - StepF15 5.39e-02 0.0176 Inf 3.054 0.1747
StepF11 - StepF16 8.91e-02 0.0176 Inf 5.049 0.0001
StepF11 - StepF17 8.45e-02 0.0176 Inf 4.789 0.0002
StepF11 - StepF18 1.10e-01 0.0177 Inf 6.248 <.0001
StepF12 - StepF13 -1.16e-02 0.0176 Inf -0.656 1.0000
StepF12 - StepF14 -2.49e-02 0.0176 Inf -1.412 0.9953
StepF12 - StepF15 -5.79e-02 0.0176 Inf -3.283 0.0940
StepF12 - StepF16 -2.27e-02 0.0176 Inf -1.288 0.9984
StepF12 - StepF17 -2.73e-02 0.0176 Inf -1.548 0.9871
StepF12 - StepF18 -1.47e-03 0.0177 Inf -0.083 1.0000
StepF13 - StepF14 -1.33e-02 0.0176 Inf -0.756 1.0000
StepF13 - StepF15 -4.64e-02 0.0176 Inf -2.627 0.4332
StepF13 - StepF16 -1.12e-02 0.0176 Inf -0.632 1.0000
StepF13 - StepF17 -1.57e-02 0.0176 Inf -0.892 1.0000
StepF13 - StepF18 1.01e-02 0.0177 Inf 0.572 1.0000
StepF14 - StepF15 -3.30e-02 0.0176 Inf -1.871 0.9227
StepF14 - StepF16 2.19e-03 0.0176 Inf 0.124 1.0000
StepF14 - StepF17 -2.40e-03 0.0176 Inf -0.136 1.0000
StepF14 - StepF18 2.34e-02 0.0177 Inf 1.327 0.9977
StepF15 - StepF16 3.52e-02 0.0176 Inf 1.995 0.8724
StepF15 - StepF17 3.06e-02 0.0176 Inf 1.735 0.9601
StepF15 - StepF18 5.65e-02 0.0177 Inf 3.196 0.1201
StepF16 - StepF17 -4.58e-03 0.0176 Inf -0.260 1.0000
StepF16 - StepF18 2.13e-02 0.0177 Inf 1.204 0.9993
StepF17 - StepF18 2.58e-02 0.0177 Inf 1.463 0.9930
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.09017 0.0176 Inf 5.110 <.0001
StepF3 - StepF2 0.01796 0.0176 Inf 1.018 1.0000
StepF4 - StepF3 -0.10642 0.0176 Inf -6.031 <.0001
StepF5 - StepF4 0.00796 0.0176 Inf 0.451 1.0000
StepF6 - StepF5 0.02911 0.0176 Inf 1.650 0.9901
StepF7 - StepF6 0.02125 0.0176 Inf 1.204 1.0000
StepF8 - StepF7 -0.07508 0.0176 Inf -4.255 0.0003
StepF9 - StepF8 0.01896 0.0176 Inf 1.074 1.0000
StepF10 - StepF9 0.04847 0.0176 Inf 2.747 0.0782
StepF11 - StepF10 0.00321 0.0176 Inf 0.182 1.0000
StepF12 - StepF11 -0.11182 0.0176 Inf -6.337 <.0001
StepF13 - StepF12 0.01158 0.0176 Inf 0.656 1.0000
StepF14 - StepF13 0.01334 0.0176 Inf 0.756 1.0000
StepF15 - StepF14 0.03301 0.0176 Inf 1.871 0.6751
StepF16 - StepF15 -0.03520 0.0176 Inf -1.995 0.5529
StepF17 - StepF16 0.00458 0.0176 Inf 0.260 1.0000
StepF18 - StepF17 -0.02584 0.0177 Inf -1.463 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.09017 0.0176 Inf 5.110 <.0001
StepF3 - StepF2 0.01796 0.0176 Inf 1.018 1.0000
StepF4 - StepF3 -0.10642 0.0176 Inf -6.031 <.0001
StepF5 - StepF4 0.00796 0.0176 Inf 0.451 1.0000
StepF6 - StepF5 0.02911 0.0176 Inf 1.650 0.9901
StepF7 - StepF6 0.02125 0.0176 Inf 1.204 1.0000
StepF8 - StepF7 -0.07508 0.0176 Inf -4.255 0.0003
StepF9 - StepF8 0.01896 0.0176 Inf 1.074 1.0000
StepF10 - StepF9 0.04847 0.0176 Inf 2.747 0.0782
StepF11 - StepF10 0.00321 0.0176 Inf 0.182 1.0000
StepF12 - StepF11 -0.11182 0.0176 Inf -6.337 <.0001
StepF13 - StepF12 0.01158 0.0176 Inf 0.656 1.0000
StepF14 - StepF13 0.01334 0.0176 Inf 0.756 1.0000
StepF15 - StepF14 0.03301 0.0176 Inf 1.871 0.6751
StepF16 - StepF15 -0.03520 0.0176 Inf -1.995 0.5529
StepF17 - StepF16 0.00458 0.0176 Inf 0.260 1.0000
StepF18 - StepF17 -0.02584 0.0177 Inf -1.463 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests
==============================
TRAINING | Block 3 (18 steps) | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 257.8478 17 <2e-16 ***
Accuracy 0.2421 1 0.6227
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.20 0.119 Inf 0.966 1.43
2 1.36 0.119 Inf 1.130 1.60
3 1.36 0.119 Inf 1.131 1.60
4 1.23 0.119 Inf 0.996 1.46
5 1.24 0.119 Inf 1.006 1.47
6 1.27 0.119 Inf 1.034 1.50
7 1.27 0.119 Inf 1.039 1.51
8 1.25 0.119 Inf 1.020 1.49
9 1.22 0.119 Inf 0.984 1.45
10 1.26 0.119 Inf 1.027 1.49
11 1.22 0.119 Inf 0.991 1.46
12 1.11 0.119 Inf 0.877 1.34
13 1.16 0.119 Inf 0.928 1.39
14 1.22 0.119 Inf 0.985 1.45
15 1.17 0.119 Inf 0.934 1.40
16 1.11 0.119 Inf 0.881 1.35
17 1.08 0.119 Inf 0.848 1.31
18 1.04 0.119 Inf 0.806 1.27
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.19 0.119 Inf 0.958 1.42
2 1.36 0.119 Inf 1.122 1.59
3 1.36 0.119 Inf 1.124 1.59
4 1.22 0.119 Inf 0.989 1.45
5 1.23 0.119 Inf 0.998 1.46
6 1.26 0.119 Inf 1.027 1.49
7 1.26 0.119 Inf 1.032 1.50
8 1.25 0.119 Inf 1.013 1.48
9 1.21 0.119 Inf 0.977 1.44
10 1.25 0.119 Inf 1.020 1.49
11 1.22 0.119 Inf 0.983 1.45
12 1.10 0.119 Inf 0.870 1.34
13 1.15 0.119 Inf 0.921 1.39
14 1.21 0.119 Inf 0.977 1.44
15 1.16 0.119 Inf 0.926 1.39
16 1.11 0.119 Inf 0.874 1.34
17 1.07 0.119 Inf 0.841 1.31
18 1.03 0.119 Inf 0.798 1.26
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.16413 0.0317 Inf -5.178 <.0001
StepF1 - StepF3 -0.16549 0.0317 Inf -5.221 <.0001
StepF1 - StepF4 -0.03047 0.0317 Inf -0.961 1.0000
StepF1 - StepF5 -0.04012 0.0317 Inf -1.266 0.9987
StepF1 - StepF6 -0.06876 0.0317 Inf -2.170 0.7741
StepF1 - StepF7 -0.07379 0.0317 Inf -2.328 0.6627
StepF1 - StepF8 -0.05473 0.0317 Inf -1.727 0.9618
StepF1 - StepF9 -0.01876 0.0317 Inf -0.592 1.0000
StepF1 - StepF10 -0.06141 0.0317 Inf -1.937 0.8977
StepF1 - StepF11 -0.02527 0.0317 Inf -0.797 1.0000
StepF1 - StepF12 0.08853 0.0317 Inf 2.793 0.3170
StepF1 - StepF13 0.03764 0.0317 Inf 1.187 0.9994
StepF1 - StepF14 -0.01911 0.0317 Inf -0.603 1.0000
StepF1 - StepF15 0.03204 0.0317 Inf 1.011 0.9999
StepF1 - StepF16 0.08454 0.0317 Inf 2.667 0.4037
StepF1 - StepF17 0.11743 0.0317 Inf 3.705 0.0240
StepF1 - StepF18 0.15973 0.0317 Inf 5.035 0.0001
StepF2 - StepF3 -0.00137 0.0317 Inf -0.043 1.0000
StepF2 - StepF4 0.13366 0.0317 Inf 4.217 0.0033
StepF2 - StepF5 0.12401 0.0317 Inf 3.913 0.0112
StepF2 - StepF6 0.09536 0.0317 Inf 3.009 0.1957
StepF2 - StepF7 0.09034 0.0317 Inf 2.850 0.2814
StepF2 - StepF8 0.10939 0.0317 Inf 3.451 0.0563
StepF2 - StepF9 0.14537 0.0317 Inf 4.586 0.0006
StepF2 - StepF10 0.10272 0.0317 Inf 3.241 0.1061
StepF2 - StepF11 0.13886 0.0317 Inf 4.381 0.0016
StepF2 - StepF12 0.25266 0.0317 Inf 7.972 <.0001
StepF2 - StepF13 0.20176 0.0317 Inf 6.366 <.0001
StepF2 - StepF14 0.14502 0.0317 Inf 4.575 0.0007
StepF2 - StepF15 0.19617 0.0317 Inf 6.189 <.0001
StepF2 - StepF16 0.24866 0.0317 Inf 7.845 <.0001
StepF2 - StepF17 0.28156 0.0317 Inf 8.883 <.0001
StepF2 - StepF18 0.32386 0.0317 Inf 10.209 <.0001
StepF3 - StepF4 0.13503 0.0317 Inf 4.260 0.0027
StepF3 - StepF5 0.12538 0.0317 Inf 3.956 0.0095
StepF3 - StepF6 0.09673 0.0317 Inf 3.052 0.1759
StepF3 - StepF7 0.09170 0.0317 Inf 2.893 0.2561
StepF3 - StepF8 0.11076 0.0317 Inf 3.495 0.0491
StepF3 - StepF9 0.14673 0.0317 Inf 4.629 0.0005
StepF3 - StepF10 0.10408 0.0317 Inf 3.284 0.0937
StepF3 - StepF11 0.14022 0.0317 Inf 4.424 0.0013
StepF3 - StepF12 0.25403 0.0317 Inf 8.015 <.0001
StepF3 - StepF13 0.20313 0.0317 Inf 6.409 <.0001
StepF3 - StepF14 0.14638 0.0317 Inf 4.618 0.0005
StepF3 - StepF15 0.19754 0.0317 Inf 6.232 <.0001
StepF3 - StepF16 0.25003 0.0317 Inf 7.888 <.0001
StepF3 - StepF17 0.28293 0.0317 Inf 8.926 <.0001
StepF3 - StepF18 0.32523 0.0317 Inf 10.252 <.0001
StepF4 - StepF5 -0.00965 0.0317 Inf -0.304 1.0000
StepF4 - StepF6 -0.03830 0.0317 Inf -1.208 0.9993
StepF4 - StepF7 -0.04332 0.0317 Inf -1.367 0.9968
StepF4 - StepF8 -0.02427 0.0317 Inf -0.766 1.0000
StepF4 - StepF9 0.01171 0.0317 Inf 0.369 1.0000
StepF4 - StepF10 -0.03094 0.0317 Inf -0.976 1.0000
StepF4 - StepF11 0.00520 0.0317 Inf 0.164 1.0000
StepF4 - StepF12 0.11900 0.0317 Inf 3.754 0.0201
StepF4 - StepF13 0.06810 0.0317 Inf 2.149 0.7873
StepF4 - StepF14 0.01136 0.0317 Inf 0.358 1.0000
StepF4 - StepF15 0.06251 0.0317 Inf 1.972 0.8827
StepF4 - StepF16 0.11500 0.0317 Inf 3.628 0.0314
StepF4 - StepF17 0.14790 0.0317 Inf 4.666 0.0004
StepF4 - StepF18 0.19020 0.0317 Inf 5.995 <.0001
StepF5 - StepF6 -0.02865 0.0317 Inf -0.904 1.0000
StepF5 - StepF7 -0.03368 0.0317 Inf -1.062 0.9999
StepF5 - StepF8 -0.01462 0.0317 Inf -0.461 1.0000
StepF5 - StepF9 0.02136 0.0317 Inf 0.674 1.0000
StepF5 - StepF10 -0.02129 0.0317 Inf -0.672 1.0000
StepF5 - StepF11 0.01484 0.0317 Inf 0.468 1.0000
StepF5 - StepF12 0.12865 0.0317 Inf 4.059 0.0063
StepF5 - StepF13 0.07775 0.0317 Inf 2.453 0.5667
StepF5 - StepF14 0.02101 0.0317 Inf 0.663 1.0000
StepF5 - StepF15 0.07216 0.0317 Inf 2.277 0.7005
StepF5 - StepF16 0.12465 0.0317 Inf 3.933 0.0103
StepF5 - StepF17 0.15755 0.0317 Inf 4.971 0.0001
StepF5 - StepF18 0.19985 0.0317 Inf 6.300 <.0001
StepF6 - StepF7 -0.00503 0.0317 Inf -0.159 1.0000
StepF6 - StepF8 0.01403 0.0317 Inf 0.443 1.0000
StepF6 - StepF9 0.05000 0.0317 Inf 1.578 0.9843
StepF6 - StepF10 0.00736 0.0317 Inf 0.232 1.0000
StepF6 - StepF11 0.04349 0.0317 Inf 1.372 0.9966
StepF6 - StepF12 0.15730 0.0317 Inf 4.963 0.0001
StepF6 - StepF13 0.10640 0.0317 Inf 3.357 0.0755
StepF6 - StepF14 0.04965 0.0317 Inf 1.567 0.9854
StepF6 - StepF15 0.10081 0.0317 Inf 3.181 0.1254
StepF6 - StepF16 0.15330 0.0317 Inf 4.837 0.0002
StepF6 - StepF17 0.18620 0.0317 Inf 5.875 <.0001
StepF6 - StepF18 0.22850 0.0317 Inf 7.203 <.0001
StepF7 - StepF8 0.01906 0.0317 Inf 0.601 1.0000
StepF7 - StepF9 0.05503 0.0317 Inf 1.736 0.9598
StepF7 - StepF10 0.01238 0.0317 Inf 0.391 1.0000
StepF7 - StepF11 0.04852 0.0317 Inf 1.531 0.9885
StepF7 - StepF12 0.16232 0.0317 Inf 5.121 <.0001
StepF7 - StepF13 0.11143 0.0317 Inf 3.516 0.0458
StepF7 - StepF14 0.05468 0.0317 Inf 1.725 0.9621
StepF7 - StepF15 0.10584 0.0317 Inf 3.339 0.0796
StepF7 - StepF16 0.15833 0.0317 Inf 4.995 0.0001
StepF7 - StepF17 0.19123 0.0317 Inf 6.033 <.0001
StepF7 - StepF18 0.23353 0.0317 Inf 7.361 <.0001
StepF8 - StepF9 0.03597 0.0317 Inf 1.135 0.9997
StepF8 - StepF10 -0.00668 0.0317 Inf -0.211 1.0000
StepF8 - StepF11 0.02946 0.0317 Inf 0.930 1.0000
StepF8 - StepF12 0.14327 0.0317 Inf 4.520 0.0009
StepF8 - StepF13 0.09237 0.0317 Inf 2.914 0.2443
StepF8 - StepF14 0.03562 0.0317 Inf 1.124 0.9997
StepF8 - StepF15 0.08678 0.0317 Inf 2.738 0.3538
StepF8 - StepF16 0.13927 0.0317 Inf 4.394 0.0015
StepF8 - StepF17 0.17217 0.0317 Inf 5.432 <.0001
StepF8 - StepF18 0.21447 0.0317 Inf 6.760 <.0001
StepF9 - StepF10 -0.04265 0.0317 Inf -1.346 0.9973
StepF9 - StepF11 -0.00651 0.0317 Inf -0.205 1.0000
StepF9 - StepF12 0.10729 0.0317 Inf 3.385 0.0693
StepF9 - StepF13 0.05640 0.0317 Inf 1.779 0.9498
StepF9 - StepF14 -0.00035 0.0317 Inf -0.011 1.0000
StepF9 - StepF15 0.05080 0.0317 Inf 1.603 0.9815
StepF9 - StepF16 0.10330 0.0317 Inf 3.259 0.1007
StepF9 - StepF17 0.13620 0.0317 Inf 4.297 0.0023
StepF9 - StepF18 0.17849 0.0317 Inf 5.626 <.0001
StepF10 - StepF11 0.03614 0.0317 Inf 1.140 0.9997
StepF10 - StepF12 0.14994 0.0317 Inf 4.731 0.0003
StepF10 - StepF13 0.09905 0.0317 Inf 3.125 0.1457
StepF10 - StepF14 0.04230 0.0317 Inf 1.335 0.9976
StepF10 - StepF15 0.09345 0.0317 Inf 2.949 0.2258
StepF10 - StepF16 0.14594 0.0317 Inf 4.605 0.0006
StepF10 - StepF17 0.17884 0.0317 Inf 5.643 <.0001
StepF10 - StepF18 0.22114 0.0317 Inf 6.971 <.0001
StepF11 - StepF12 0.11380 0.0317 Inf 3.591 0.0357
StepF11 - StepF13 0.06291 0.0317 Inf 1.985 0.8770
StepF11 - StepF14 0.00616 0.0317 Inf 0.194 1.0000
StepF11 - StepF15 0.05732 0.0317 Inf 1.808 0.9421
StepF11 - StepF16 0.10981 0.0317 Inf 3.464 0.0540
StepF11 - StepF17 0.14271 0.0317 Inf 4.502 0.0009
StepF11 - StepF18 0.18501 0.0317 Inf 5.832 <.0001
StepF12 - StepF13 -0.05090 0.0317 Inf -1.606 0.9811
StepF12 - StepF14 -0.10764 0.0317 Inf -3.396 0.0670
StepF12 - StepF15 -0.05649 0.0317 Inf -1.782 0.9490
StepF12 - StepF16 -0.00400 0.0317 Inf -0.126 1.0000
StepF12 - StepF17 0.02890 0.0317 Inf 0.912 1.0000
StepF12 - StepF18 0.07120 0.0317 Inf 2.244 0.7236
StepF13 - StepF14 -0.05675 0.0317 Inf -1.790 0.9469
StepF13 - StepF15 -0.00559 0.0317 Inf -0.176 1.0000
StepF13 - StepF16 0.04690 0.0317 Inf 1.480 0.9921
StepF13 - StepF17 0.07980 0.0317 Inf 2.518 0.5165
StepF13 - StepF18 0.12210 0.0317 Inf 3.849 0.0142
StepF14 - StepF15 0.05115 0.0317 Inf 1.614 0.9801
StepF14 - StepF16 0.10365 0.0317 Inf 3.270 0.0976
StepF14 - StepF17 0.13654 0.0317 Inf 4.308 0.0022
StepF14 - StepF18 0.17884 0.0317 Inf 5.637 <.0001
StepF15 - StepF16 0.05249 0.0317 Inf 1.656 0.9743
StepF15 - StepF17 0.08539 0.0317 Inf 2.694 0.3843
StepF15 - StepF18 0.12769 0.0317 Inf 4.025 0.0072
StepF16 - StepF17 0.03290 0.0317 Inf 1.038 0.9999
StepF16 - StepF18 0.07520 0.0317 Inf 2.370 0.6307
StepF17 - StepF18 0.04230 0.0317 Inf 1.333 0.9976
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.16413 0.0317 Inf -5.178 <.0001
StepF1 - StepF3 -0.16549 0.0317 Inf -5.221 <.0001
StepF1 - StepF4 -0.03047 0.0317 Inf -0.961 1.0000
StepF1 - StepF5 -0.04012 0.0317 Inf -1.266 0.9987
StepF1 - StepF6 -0.06876 0.0317 Inf -2.170 0.7741
StepF1 - StepF7 -0.07379 0.0317 Inf -2.328 0.6627
StepF1 - StepF8 -0.05473 0.0317 Inf -1.727 0.9618
StepF1 - StepF9 -0.01876 0.0317 Inf -0.592 1.0000
StepF1 - StepF10 -0.06141 0.0317 Inf -1.937 0.8977
StepF1 - StepF11 -0.02527 0.0317 Inf -0.797 1.0000
StepF1 - StepF12 0.08853 0.0317 Inf 2.793 0.3170
StepF1 - StepF13 0.03764 0.0317 Inf 1.187 0.9994
StepF1 - StepF14 -0.01911 0.0317 Inf -0.603 1.0000
StepF1 - StepF15 0.03204 0.0317 Inf 1.011 0.9999
StepF1 - StepF16 0.08454 0.0317 Inf 2.667 0.4037
StepF1 - StepF17 0.11743 0.0317 Inf 3.705 0.0240
StepF1 - StepF18 0.15973 0.0317 Inf 5.035 0.0001
StepF2 - StepF3 -0.00137 0.0317 Inf -0.043 1.0000
StepF2 - StepF4 0.13366 0.0317 Inf 4.217 0.0033
StepF2 - StepF5 0.12401 0.0317 Inf 3.913 0.0112
StepF2 - StepF6 0.09536 0.0317 Inf 3.009 0.1957
StepF2 - StepF7 0.09034 0.0317 Inf 2.850 0.2814
StepF2 - StepF8 0.10939 0.0317 Inf 3.451 0.0563
StepF2 - StepF9 0.14537 0.0317 Inf 4.586 0.0006
StepF2 - StepF10 0.10272 0.0317 Inf 3.241 0.1061
StepF2 - StepF11 0.13886 0.0317 Inf 4.381 0.0016
StepF2 - StepF12 0.25266 0.0317 Inf 7.972 <.0001
StepF2 - StepF13 0.20176 0.0317 Inf 6.366 <.0001
StepF2 - StepF14 0.14502 0.0317 Inf 4.575 0.0007
StepF2 - StepF15 0.19617 0.0317 Inf 6.189 <.0001
StepF2 - StepF16 0.24866 0.0317 Inf 7.845 <.0001
StepF2 - StepF17 0.28156 0.0317 Inf 8.883 <.0001
StepF2 - StepF18 0.32386 0.0317 Inf 10.209 <.0001
StepF3 - StepF4 0.13503 0.0317 Inf 4.260 0.0027
StepF3 - StepF5 0.12538 0.0317 Inf 3.956 0.0095
StepF3 - StepF6 0.09673 0.0317 Inf 3.052 0.1759
StepF3 - StepF7 0.09170 0.0317 Inf 2.893 0.2561
StepF3 - StepF8 0.11076 0.0317 Inf 3.495 0.0491
StepF3 - StepF9 0.14673 0.0317 Inf 4.629 0.0005
StepF3 - StepF10 0.10408 0.0317 Inf 3.284 0.0937
StepF3 - StepF11 0.14022 0.0317 Inf 4.424 0.0013
StepF3 - StepF12 0.25403 0.0317 Inf 8.015 <.0001
StepF3 - StepF13 0.20313 0.0317 Inf 6.409 <.0001
StepF3 - StepF14 0.14638 0.0317 Inf 4.618 0.0005
StepF3 - StepF15 0.19754 0.0317 Inf 6.232 <.0001
StepF3 - StepF16 0.25003 0.0317 Inf 7.888 <.0001
StepF3 - StepF17 0.28293 0.0317 Inf 8.926 <.0001
StepF3 - StepF18 0.32523 0.0317 Inf 10.252 <.0001
StepF4 - StepF5 -0.00965 0.0317 Inf -0.304 1.0000
StepF4 - StepF6 -0.03830 0.0317 Inf -1.208 0.9993
StepF4 - StepF7 -0.04332 0.0317 Inf -1.367 0.9968
StepF4 - StepF8 -0.02427 0.0317 Inf -0.766 1.0000
StepF4 - StepF9 0.01171 0.0317 Inf 0.369 1.0000
StepF4 - StepF10 -0.03094 0.0317 Inf -0.976 1.0000
StepF4 - StepF11 0.00520 0.0317 Inf 0.164 1.0000
StepF4 - StepF12 0.11900 0.0317 Inf 3.754 0.0201
StepF4 - StepF13 0.06810 0.0317 Inf 2.149 0.7873
StepF4 - StepF14 0.01136 0.0317 Inf 0.358 1.0000
StepF4 - StepF15 0.06251 0.0317 Inf 1.972 0.8827
StepF4 - StepF16 0.11500 0.0317 Inf 3.628 0.0314
StepF4 - StepF17 0.14790 0.0317 Inf 4.666 0.0004
StepF4 - StepF18 0.19020 0.0317 Inf 5.995 <.0001
StepF5 - StepF6 -0.02865 0.0317 Inf -0.904 1.0000
StepF5 - StepF7 -0.03368 0.0317 Inf -1.062 0.9999
StepF5 - StepF8 -0.01462 0.0317 Inf -0.461 1.0000
StepF5 - StepF9 0.02136 0.0317 Inf 0.674 1.0000
StepF5 - StepF10 -0.02129 0.0317 Inf -0.672 1.0000
StepF5 - StepF11 0.01484 0.0317 Inf 0.468 1.0000
StepF5 - StepF12 0.12865 0.0317 Inf 4.059 0.0063
StepF5 - StepF13 0.07775 0.0317 Inf 2.453 0.5667
StepF5 - StepF14 0.02101 0.0317 Inf 0.663 1.0000
StepF5 - StepF15 0.07216 0.0317 Inf 2.277 0.7005
StepF5 - StepF16 0.12465 0.0317 Inf 3.933 0.0103
StepF5 - StepF17 0.15755 0.0317 Inf 4.971 0.0001
StepF5 - StepF18 0.19985 0.0317 Inf 6.300 <.0001
StepF6 - StepF7 -0.00503 0.0317 Inf -0.159 1.0000
StepF6 - StepF8 0.01403 0.0317 Inf 0.443 1.0000
StepF6 - StepF9 0.05000 0.0317 Inf 1.578 0.9843
StepF6 - StepF10 0.00736 0.0317 Inf 0.232 1.0000
StepF6 - StepF11 0.04349 0.0317 Inf 1.372 0.9966
StepF6 - StepF12 0.15730 0.0317 Inf 4.963 0.0001
StepF6 - StepF13 0.10640 0.0317 Inf 3.357 0.0755
StepF6 - StepF14 0.04965 0.0317 Inf 1.567 0.9854
StepF6 - StepF15 0.10081 0.0317 Inf 3.181 0.1254
StepF6 - StepF16 0.15330 0.0317 Inf 4.837 0.0002
StepF6 - StepF17 0.18620 0.0317 Inf 5.875 <.0001
StepF6 - StepF18 0.22850 0.0317 Inf 7.203 <.0001
StepF7 - StepF8 0.01906 0.0317 Inf 0.601 1.0000
StepF7 - StepF9 0.05503 0.0317 Inf 1.736 0.9598
StepF7 - StepF10 0.01238 0.0317 Inf 0.391 1.0000
StepF7 - StepF11 0.04852 0.0317 Inf 1.531 0.9885
StepF7 - StepF12 0.16232 0.0317 Inf 5.121 <.0001
StepF7 - StepF13 0.11143 0.0317 Inf 3.516 0.0458
StepF7 - StepF14 0.05468 0.0317 Inf 1.725 0.9621
StepF7 - StepF15 0.10584 0.0317 Inf 3.339 0.0796
StepF7 - StepF16 0.15833 0.0317 Inf 4.995 0.0001
StepF7 - StepF17 0.19123 0.0317 Inf 6.033 <.0001
StepF7 - StepF18 0.23353 0.0317 Inf 7.361 <.0001
StepF8 - StepF9 0.03597 0.0317 Inf 1.135 0.9997
StepF8 - StepF10 -0.00668 0.0317 Inf -0.211 1.0000
StepF8 - StepF11 0.02946 0.0317 Inf 0.930 1.0000
StepF8 - StepF12 0.14327 0.0317 Inf 4.520 0.0009
StepF8 - StepF13 0.09237 0.0317 Inf 2.914 0.2443
StepF8 - StepF14 0.03562 0.0317 Inf 1.124 0.9997
StepF8 - StepF15 0.08678 0.0317 Inf 2.738 0.3538
StepF8 - StepF16 0.13927 0.0317 Inf 4.394 0.0015
StepF8 - StepF17 0.17217 0.0317 Inf 5.432 <.0001
StepF8 - StepF18 0.21447 0.0317 Inf 6.760 <.0001
StepF9 - StepF10 -0.04265 0.0317 Inf -1.346 0.9973
StepF9 - StepF11 -0.00651 0.0317 Inf -0.205 1.0000
StepF9 - StepF12 0.10729 0.0317 Inf 3.385 0.0693
StepF9 - StepF13 0.05640 0.0317 Inf 1.779 0.9498
StepF9 - StepF14 -0.00035 0.0317 Inf -0.011 1.0000
StepF9 - StepF15 0.05080 0.0317 Inf 1.603 0.9815
StepF9 - StepF16 0.10330 0.0317 Inf 3.259 0.1007
StepF9 - StepF17 0.13620 0.0317 Inf 4.297 0.0023
StepF9 - StepF18 0.17849 0.0317 Inf 5.626 <.0001
StepF10 - StepF11 0.03614 0.0317 Inf 1.140 0.9997
StepF10 - StepF12 0.14994 0.0317 Inf 4.731 0.0003
StepF10 - StepF13 0.09905 0.0317 Inf 3.125 0.1457
StepF10 - StepF14 0.04230 0.0317 Inf 1.335 0.9976
StepF10 - StepF15 0.09345 0.0317 Inf 2.949 0.2258
StepF10 - StepF16 0.14594 0.0317 Inf 4.605 0.0006
StepF10 - StepF17 0.17884 0.0317 Inf 5.643 <.0001
StepF10 - StepF18 0.22114 0.0317 Inf 6.971 <.0001
StepF11 - StepF12 0.11380 0.0317 Inf 3.591 0.0357
StepF11 - StepF13 0.06291 0.0317 Inf 1.985 0.8770
StepF11 - StepF14 0.00616 0.0317 Inf 0.194 1.0000
StepF11 - StepF15 0.05732 0.0317 Inf 1.808 0.9421
StepF11 - StepF16 0.10981 0.0317 Inf 3.464 0.0540
StepF11 - StepF17 0.14271 0.0317 Inf 4.502 0.0009
StepF11 - StepF18 0.18501 0.0317 Inf 5.832 <.0001
StepF12 - StepF13 -0.05090 0.0317 Inf -1.606 0.9811
StepF12 - StepF14 -0.10764 0.0317 Inf -3.396 0.0670
StepF12 - StepF15 -0.05649 0.0317 Inf -1.782 0.9490
StepF12 - StepF16 -0.00400 0.0317 Inf -0.126 1.0000
StepF12 - StepF17 0.02890 0.0317 Inf 0.912 1.0000
StepF12 - StepF18 0.07120 0.0317 Inf 2.244 0.7236
StepF13 - StepF14 -0.05675 0.0317 Inf -1.790 0.9469
StepF13 - StepF15 -0.00559 0.0317 Inf -0.176 1.0000
StepF13 - StepF16 0.04690 0.0317 Inf 1.480 0.9921
StepF13 - StepF17 0.07980 0.0317 Inf 2.518 0.5165
StepF13 - StepF18 0.12210 0.0317 Inf 3.849 0.0142
StepF14 - StepF15 0.05115 0.0317 Inf 1.614 0.9801
StepF14 - StepF16 0.10365 0.0317 Inf 3.270 0.0976
StepF14 - StepF17 0.13654 0.0317 Inf 4.308 0.0022
StepF14 - StepF18 0.17884 0.0317 Inf 5.637 <.0001
StepF15 - StepF16 0.05249 0.0317 Inf 1.656 0.9743
StepF15 - StepF17 0.08539 0.0317 Inf 2.694 0.3843
StepF15 - StepF18 0.12769 0.0317 Inf 4.025 0.0072
StepF16 - StepF17 0.03290 0.0317 Inf 1.038 0.9999
StepF16 - StepF18 0.07520 0.0317 Inf 2.370 0.6307
StepF17 - StepF18 0.04230 0.0317 Inf 1.333 0.9976
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.16413 0.0317 Inf 5.178 <.0001
StepF3 - StepF2 0.00137 0.0317 Inf 0.043 1.0000
StepF4 - StepF3 -0.13503 0.0317 Inf -4.260 0.0003
StepF5 - StepF4 0.00965 0.0317 Inf 0.304 1.0000
StepF6 - StepF5 0.02865 0.0317 Inf 0.904 1.0000
StepF7 - StepF6 0.00503 0.0317 Inf 0.159 1.0000
StepF8 - StepF7 -0.01906 0.0317 Inf -0.601 1.0000
StepF9 - StepF8 -0.03597 0.0317 Inf -1.135 1.0000
StepF10 - StepF9 0.04265 0.0317 Inf 1.346 1.0000
StepF11 - StepF10 -0.03614 0.0317 Inf -1.140 1.0000
StepF12 - StepF11 -0.11380 0.0317 Inf -3.591 0.0049
StepF13 - StepF12 0.05090 0.0317 Inf 1.606 1.0000
StepF14 - StepF13 0.05675 0.0317 Inf 1.790 1.0000
StepF15 - StepF14 -0.05115 0.0317 Inf -1.614 1.0000
StepF16 - StepF15 -0.05249 0.0317 Inf -1.656 1.0000
StepF17 - StepF16 -0.03290 0.0317 Inf -1.038 1.0000
StepF18 - StepF17 -0.04230 0.0317 Inf -1.333 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.16413 0.0317 Inf 5.178 <.0001
StepF3 - StepF2 0.00137 0.0317 Inf 0.043 1.0000
StepF4 - StepF3 -0.13503 0.0317 Inf -4.260 0.0003
StepF5 - StepF4 0.00965 0.0317 Inf 0.304 1.0000
StepF6 - StepF5 0.02865 0.0317 Inf 0.904 1.0000
StepF7 - StepF6 0.00503 0.0317 Inf 0.159 1.0000
StepF8 - StepF7 -0.01906 0.0317 Inf -0.601 1.0000
StepF9 - StepF8 -0.03597 0.0317 Inf -1.135 1.0000
StepF10 - StepF9 0.04265 0.0317 Inf 1.346 1.0000
StepF11 - StepF10 -0.03614 0.0317 Inf -1.140 1.0000
StepF12 - StepF11 -0.11380 0.0317 Inf -3.591 0.0049
StepF13 - StepF12 0.05090 0.0317 Inf 1.606 1.0000
StepF14 - StepF13 0.05675 0.0317 Inf 1.790 1.0000
StepF15 - StepF14 -0.05115 0.0317 Inf -1.614 1.0000
StepF16 - StepF15 -0.05249 0.0317 Inf -1.656 1.0000
StepF17 - StepF16 -0.03290 0.0317 Inf -1.038 1.0000
StepF18 - StepF17 -0.04230 0.0317 Inf -1.333 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests # ==== TEST (Blocks 4–5): stepwise LMM + χ² + EMMs + all-pairs + adjacent (per block × seq length × axis)
suppressPackageStartupMessages({
library(dplyr); library(lme4); library(lmerTest); library(emmeans); library(car)
})
emm_options(lmer.df = "asymptotic")
.report_step_test <- function(df_block, block_label, seq_label) {
for (ax in c("x","y","z")) {
dd <- df_block %>% filter(Axis == ax)
if (nrow(dd) == 0) next
dd <- dd %>%
mutate(
StepF = factor(Step, levels = sort(unique(Step))),
subject = factor(subject),
trial_id = factor(trial_id),
Accuracy = droplevels(Accuracy)
)
cat("\n\n==============================\n",
"TEST | Block ", block_label, " | ", seq_label, " | Axis ", toupper(ax),
"\n==============================\n", sep = "")
m <- suppressWarnings(lmer(RMS ~ StepF + Accuracy + (1|subject) + (1|trial_id),
data = dd, REML = TRUE))
cat("\nType II Wald χ² (StepF & Accuracy):\n")
print(car::Anova(m, type = 2, test.statistic = "Chisq"))
if (nlevels(dd$Accuracy) >= 2) {
em <- emmeans(m, ~ StepF | Accuracy)
cat("\nEMMs per step | Accuracy:\n"); print(summary(em))
cat("\nAll-pairs (Tukey) among steps | Accuracy:\n")
print(pairs(em, adjust = "tukey"))
cat("\nAdjacent steps (consec; Holm) | Accuracy:\n")
print(contrast(em, method = "consec", by = "Accuracy", adjust = "holm"))
} else {
em <- emmeans(m, ~ StepF)
cat("\nEMMs per step:\n"); print(summary(em))
cat("\nAll-pairs (Tukey) among steps:\n")
print(pairs(em, adjust = "tukey"))
cat("\nAdjacent steps (consec; Holm):\n")
print(contrast(em, method = "consec", adjust = "holm"))
}
rm(m, em); invisible(gc())
}
}
# Block 4
.report_step_test(sw_b4_6, "4", "6 steps")
==============================
TEST | Block 4 | 6 steps | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 67.6532 5 3.153e-13 ***
Accuracy 0.1616 1 0.6877
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.684 0.0717 Inf 0.543 0.824
2 0.785 0.0717 Inf 0.644 0.925
3 0.785 0.0717 Inf 0.645 0.926
4 0.738 0.0717 Inf 0.598 0.879
5 0.599 0.0717 Inf 0.458 0.739
6 0.627 0.0717 Inf 0.487 0.768
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.674 0.0702 Inf 0.537 0.812
2 0.775 0.0702 Inf 0.638 0.913
3 0.776 0.0702 Inf 0.639 0.914
4 0.729 0.0702 Inf 0.592 0.867
5 0.589 0.0702 Inf 0.452 0.727
6 0.618 0.0702 Inf 0.480 0.755
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.100977 0.0306 Inf -3.295 0.0126
StepF1 - StepF3 -0.101660 0.0306 Inf -3.318 0.0117
StepF1 - StepF4 -0.054661 0.0306 Inf -1.784 0.4762
StepF1 - StepF5 0.085246 0.0306 Inf 2.782 0.0603
StepF1 - StepF6 0.056560 0.0306 Inf 1.846 0.4361
StepF2 - StepF3 -0.000683 0.0306 Inf -0.022 1.0000
StepF2 - StepF4 0.046316 0.0306 Inf 1.512 0.6568
StepF2 - StepF5 0.186222 0.0306 Inf 6.077 <.0001
StepF2 - StepF6 0.157537 0.0306 Inf 5.141 <.0001
StepF3 - StepF4 0.046999 0.0306 Inf 1.534 0.6423
StepF3 - StepF5 0.186906 0.0306 Inf 6.100 <.0001
StepF3 - StepF6 0.158220 0.0306 Inf 5.163 <.0001
StepF4 - StepF5 0.139906 0.0306 Inf 4.566 0.0001
StepF4 - StepF6 0.111221 0.0306 Inf 3.630 0.0039
StepF5 - StepF6 -0.028686 0.0306 Inf -0.936 0.9372
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.100977 0.0306 Inf -3.295 0.0126
StepF1 - StepF3 -0.101660 0.0306 Inf -3.318 0.0117
StepF1 - StepF4 -0.054661 0.0306 Inf -1.784 0.4762
StepF1 - StepF5 0.085246 0.0306 Inf 2.782 0.0603
StepF1 - StepF6 0.056560 0.0306 Inf 1.846 0.4361
StepF2 - StepF3 -0.000683 0.0306 Inf -0.022 1.0000
StepF2 - StepF4 0.046316 0.0306 Inf 1.512 0.6568
StepF2 - StepF5 0.186222 0.0306 Inf 6.077 <.0001
StepF2 - StepF6 0.157537 0.0306 Inf 5.141 <.0001
StepF3 - StepF4 0.046999 0.0306 Inf 1.534 0.6423
StepF3 - StepF5 0.186906 0.0306 Inf 6.100 <.0001
StepF3 - StepF6 0.158220 0.0306 Inf 5.163 <.0001
StepF4 - StepF5 0.139906 0.0306 Inf 4.566 0.0001
StepF4 - StepF6 0.111221 0.0306 Inf 3.630 0.0039
StepF5 - StepF6 -0.028686 0.0306 Inf -0.936 0.9372
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.100977 0.0306 Inf 3.295 0.0039
StepF3 - StepF2 0.000683 0.0306 Inf 0.022 0.9822
StepF4 - StepF3 -0.046999 0.0306 Inf -1.534 0.3752
StepF5 - StepF4 -0.139906 0.0306 Inf -4.566 <.0001
StepF6 - StepF5 0.028686 0.0306 Inf 0.936 0.6984
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.100977 0.0306 Inf 3.295 0.0039
StepF3 - StepF2 0.000683 0.0306 Inf 0.022 0.9822
StepF4 - StepF3 -0.046999 0.0306 Inf -1.534 0.3752
StepF5 - StepF4 -0.139906 0.0306 Inf -4.566 <.0001
StepF6 - StepF5 0.028686 0.0306 Inf 0.936 0.6984
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests
==============================
TEST | Block 4 | 6 steps | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 69.9093 5 1.07e-13 ***
Accuracy 0.0123 1 0.9117
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.688 0.0863 Inf 0.519 0.857
2 0.906 0.0863 Inf 0.737 1.075
3 0.864 0.0863 Inf 0.695 1.034
4 0.762 0.0863 Inf 0.593 0.931
5 0.688 0.0863 Inf 0.519 0.857
6 0.743 0.0863 Inf 0.574 0.912
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.685 0.0847 Inf 0.519 0.851
2 0.903 0.0847 Inf 0.737 1.069
3 0.862 0.0847 Inf 0.695 1.028
4 0.759 0.0847 Inf 0.593 0.925
5 0.685 0.0847 Inf 0.519 0.851
6 0.740 0.0847 Inf 0.574 0.906
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -2.18e-01 0.0345 Inf -6.328 <.0001
StepF1 - StepF3 -1.77e-01 0.0345 Inf -5.120 <.0001
StepF1 - StepF4 -7.42e-02 0.0345 Inf -2.151 0.2610
StepF1 - StepF5 8.15e-05 0.0345 Inf 0.002 1.0000
StepF1 - StepF6 -5.52e-02 0.0345 Inf -1.600 0.5986
StepF2 - StepF3 4.16e-02 0.0345 Inf 1.208 0.8334
StepF2 - StepF4 1.44e-01 0.0345 Inf 4.177 0.0004
StepF2 - StepF5 2.18e-01 0.0345 Inf 6.330 <.0001
StepF2 - StepF6 1.63e-01 0.0345 Inf 4.728 <.0001
StepF3 - StepF4 1.02e-01 0.0345 Inf 2.969 0.0354
StepF3 - StepF5 1.77e-01 0.0345 Inf 5.123 <.0001
StepF3 - StepF6 1.21e-01 0.0345 Inf 3.520 0.0058
StepF4 - StepF5 7.43e-02 0.0345 Inf 2.154 0.2599
StepF4 - StepF6 1.90e-02 0.0345 Inf 0.551 0.9940
StepF5 - StepF6 -5.52e-02 0.0345 Inf -1.602 0.5970
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -2.18e-01 0.0345 Inf -6.328 <.0001
StepF1 - StepF3 -1.77e-01 0.0345 Inf -5.120 <.0001
StepF1 - StepF4 -7.42e-02 0.0345 Inf -2.151 0.2610
StepF1 - StepF5 8.15e-05 0.0345 Inf 0.002 1.0000
StepF1 - StepF6 -5.52e-02 0.0345 Inf -1.600 0.5986
StepF2 - StepF3 4.16e-02 0.0345 Inf 1.208 0.8334
StepF2 - StepF4 1.44e-01 0.0345 Inf 4.177 0.0004
StepF2 - StepF5 2.18e-01 0.0345 Inf 6.330 <.0001
StepF2 - StepF6 1.63e-01 0.0345 Inf 4.728 <.0001
StepF3 - StepF4 1.02e-01 0.0345 Inf 2.969 0.0354
StepF3 - StepF5 1.77e-01 0.0345 Inf 5.123 <.0001
StepF3 - StepF6 1.21e-01 0.0345 Inf 3.520 0.0058
StepF4 - StepF5 7.43e-02 0.0345 Inf 2.154 0.2599
StepF4 - StepF6 1.90e-02 0.0345 Inf 0.551 0.9940
StepF5 - StepF6 -5.52e-02 0.0345 Inf -1.602 0.5970
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2182 0.0345 Inf 6.328 <.0001
StepF3 - StepF2 -0.0416 0.0345 Inf -1.208 0.2272
StepF4 - StepF3 -0.1024 0.0345 Inf -2.969 0.0120
StepF5 - StepF4 -0.0743 0.0345 Inf -2.154 0.0938
StepF6 - StepF5 0.0552 0.0345 Inf 1.602 0.2182
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2182 0.0345 Inf 6.328 <.0001
StepF3 - StepF2 -0.0416 0.0345 Inf -1.208 0.2272
StepF4 - StepF3 -0.1024 0.0345 Inf -2.969 0.0120
StepF5 - StepF4 -0.0743 0.0345 Inf -2.154 0.0938
StepF6 - StepF5 0.0552 0.0345 Inf 1.602 0.2182
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests
==============================
TEST | Block 4 | 6 steps | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 83.2385 5 <2e-16 ***
Accuracy 0.0005 1 0.983
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.44 0.152 Inf 1.15 1.74
2 1.69 0.152 Inf 1.40 1.99
3 1.74 0.152 Inf 1.44 2.04
4 1.61 0.152 Inf 1.31 1.90
5 1.36 0.152 Inf 1.06 1.66
6 1.32 0.152 Inf 1.02 1.62
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.45 0.149 Inf 1.15 1.74
2 1.69 0.149 Inf 1.40 1.98
3 1.74 0.149 Inf 1.45 2.03
4 1.61 0.149 Inf 1.32 1.90
5 1.36 0.149 Inf 1.07 1.65
6 1.32 0.149 Inf 1.03 1.61
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.2474 0.0614 Inf -4.031 0.0008
StepF1 - StepF3 -0.2960 0.0614 Inf -4.823 <.0001
StepF1 - StepF4 -0.1626 0.0614 Inf -2.650 0.0855
StepF1 - StepF5 0.0831 0.0614 Inf 1.354 0.7548
StepF1 - StepF6 0.1257 0.0614 Inf 2.048 0.3151
StepF2 - StepF3 -0.0486 0.0614 Inf -0.791 0.9691
StepF2 - StepF4 0.0848 0.0614 Inf 1.381 0.7385
StepF2 - StepF5 0.3305 0.0614 Inf 5.385 <.0001
StepF2 - StepF6 0.3731 0.0614 Inf 6.079 <.0001
StepF3 - StepF4 0.1333 0.0614 Inf 2.172 0.2507
StepF3 - StepF5 0.3790 0.0614 Inf 6.176 <.0001
StepF3 - StepF6 0.4216 0.0614 Inf 6.871 <.0001
StepF4 - StepF5 0.2457 0.0614 Inf 4.004 0.0009
StepF4 - StepF6 0.2883 0.0614 Inf 4.698 <.0001
StepF5 - StepF6 0.0426 0.0614 Inf 0.694 0.9826
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.2474 0.0614 Inf -4.031 0.0008
StepF1 - StepF3 -0.2960 0.0614 Inf -4.823 <.0001
StepF1 - StepF4 -0.1626 0.0614 Inf -2.650 0.0855
StepF1 - StepF5 0.0831 0.0614 Inf 1.354 0.7548
StepF1 - StepF6 0.1257 0.0614 Inf 2.048 0.3151
StepF2 - StepF3 -0.0486 0.0614 Inf -0.791 0.9691
StepF2 - StepF4 0.0848 0.0614 Inf 1.381 0.7385
StepF2 - StepF5 0.3305 0.0614 Inf 5.385 <.0001
StepF2 - StepF6 0.3731 0.0614 Inf 6.079 <.0001
StepF3 - StepF4 0.1333 0.0614 Inf 2.172 0.2507
StepF3 - StepF5 0.3790 0.0614 Inf 6.176 <.0001
StepF3 - StepF6 0.4216 0.0614 Inf 6.871 <.0001
StepF4 - StepF5 0.2457 0.0614 Inf 4.004 0.0009
StepF4 - StepF6 0.2883 0.0614 Inf 4.698 <.0001
StepF5 - StepF6 0.0426 0.0614 Inf 0.694 0.9826
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2474 0.0614 Inf 4.031 0.0003
StepF3 - StepF2 0.0486 0.0614 Inf 0.791 0.8576
StepF4 - StepF3 -0.1333 0.0614 Inf -2.172 0.0895
StepF5 - StepF4 -0.2457 0.0614 Inf -4.004 0.0003
StepF6 - StepF5 -0.0426 0.0614 Inf -0.694 0.8576
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2474 0.0614 Inf 4.031 0.0003
StepF3 - StepF2 0.0486 0.0614 Inf 0.791 0.8576
StepF4 - StepF3 -0.1333 0.0614 Inf -2.172 0.0895
StepF5 - StepF4 -0.2457 0.0614 Inf -4.004 0.0003
StepF6 - StepF5 -0.0426 0.0614 Inf -0.694 0.8576
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests .report_step_test(sw_b4_12, "4", "12 steps")
==============================
TEST | Block 4 | 12 steps | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 125.9062 11 <2e-16 ***
Accuracy 0.0141 1 0.9054
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.683 0.0714 Inf 0.544 0.823
2 0.785 0.0714 Inf 0.645 0.925
3 0.774 0.0714 Inf 0.634 0.914
4 0.716 0.0714 Inf 0.576 0.856
5 0.679 0.0714 Inf 0.539 0.819
6 0.740 0.0714 Inf 0.600 0.880
7 0.724 0.0714 Inf 0.584 0.864
8 0.684 0.0714 Inf 0.544 0.824
9 0.649 0.0714 Inf 0.509 0.788
10 0.607 0.0714 Inf 0.467 0.747
11 0.625 0.0714 Inf 0.486 0.765
12 0.520 0.0714 Inf 0.380 0.660
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.686 0.0703 Inf 0.548 0.823
2 0.787 0.0703 Inf 0.650 0.925
3 0.776 0.0703 Inf 0.639 0.914
4 0.718 0.0703 Inf 0.580 0.856
5 0.681 0.0703 Inf 0.543 0.819
6 0.742 0.0703 Inf 0.605 0.880
7 0.726 0.0703 Inf 0.588 0.864
8 0.686 0.0703 Inf 0.548 0.824
9 0.651 0.0703 Inf 0.513 0.789
10 0.609 0.0703 Inf 0.471 0.747
11 0.628 0.0703 Inf 0.490 0.765
12 0.522 0.0703 Inf 0.384 0.660
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.101751 0.0313 Inf -3.249 0.0530
StepF1 - StepF3 -0.090757 0.0313 Inf -2.898 0.1415
StepF1 - StepF4 -0.032220 0.0313 Inf -1.029 0.9971
StepF1 - StepF5 0.004576 0.0313 Inf 0.146 1.0000
StepF1 - StepF6 -0.056830 0.0313 Inf -1.815 0.8104
StepF1 - StepF7 -0.040277 0.0313 Inf -1.286 0.9810
StepF1 - StepF8 -0.000245 0.0313 Inf -0.008 1.0000
StepF1 - StepF9 0.034954 0.0313 Inf 1.116 0.9941
StepF1 - StepF10 0.076751 0.0313 Inf 2.451 0.3717
StepF1 - StepF11 0.058019 0.0313 Inf 1.852 0.7885
StepF1 - StepF12 0.163683 0.0313 Inf 5.226 <.0001
StepF2 - StepF3 0.010994 0.0313 Inf 0.351 1.0000
StepF2 - StepF4 0.069531 0.0313 Inf 2.220 0.5348
StepF2 - StepF5 0.106327 0.0313 Inf 3.395 0.0334
StepF2 - StepF6 0.044921 0.0313 Inf 1.434 0.9569
StepF2 - StepF7 0.061474 0.0313 Inf 1.963 0.7189
StepF2 - StepF8 0.101505 0.0313 Inf 3.241 0.0543
StepF2 - StepF9 0.136705 0.0313 Inf 4.365 0.0008
StepF2 - StepF10 0.178502 0.0313 Inf 5.699 <.0001
StepF2 - StepF11 0.159770 0.0313 Inf 5.101 <.0001
StepF2 - StepF12 0.265434 0.0313 Inf 8.475 <.0001
StepF3 - StepF4 0.058537 0.0313 Inf 1.869 0.7787
StepF3 - StepF5 0.095332 0.0313 Inf 3.044 0.0962
StepF3 - StepF6 0.033927 0.0313 Inf 1.083 0.9954
StepF3 - StepF7 0.050480 0.0313 Inf 1.612 0.9053
StepF3 - StepF8 0.090511 0.0313 Inf 2.890 0.1443
StepF3 - StepF9 0.125711 0.0313 Inf 4.014 0.0035
StepF3 - StepF10 0.167508 0.0313 Inf 5.348 <.0001
StepF3 - StepF11 0.148776 0.0313 Inf 4.750 0.0001
StepF3 - StepF12 0.254440 0.0313 Inf 8.124 <.0001
StepF4 - StepF5 0.036796 0.0313 Inf 1.175 0.9908
StepF4 - StepF6 -0.024610 0.0313 Inf -0.786 0.9998
StepF4 - StepF7 -0.008057 0.0313 Inf -0.257 1.0000
StepF4 - StepF8 0.031975 0.0313 Inf 1.021 0.9973
StepF4 - StepF9 0.067174 0.0313 Inf 2.145 0.5901
StepF4 - StepF10 0.108971 0.0313 Inf 3.479 0.0253
StepF4 - StepF11 0.090239 0.0313 Inf 2.881 0.1475
StepF4 - StepF12 0.195903 0.0313 Inf 6.255 <.0001
StepF5 - StepF6 -0.061406 0.0313 Inf -1.961 0.7203
StepF5 - StepF7 -0.044852 0.0313 Inf -1.432 0.9574
StepF5 - StepF8 -0.004821 0.0313 Inf -0.154 1.0000
StepF5 - StepF9 0.030378 0.0313 Inf 0.970 0.9983
StepF5 - StepF10 0.072176 0.0313 Inf 2.305 0.4732
StepF5 - StepF11 0.053443 0.0313 Inf 1.706 0.8658
StepF5 - StepF12 0.159107 0.0313 Inf 5.080 <.0001
StepF6 - StepF7 0.016553 0.0313 Inf 0.529 1.0000
StepF6 - StepF8 0.056584 0.0313 Inf 1.807 0.8148
StepF6 - StepF9 0.091784 0.0313 Inf 2.931 0.1301
StepF6 - StepF10 0.133581 0.0313 Inf 4.265 0.0012
StepF6 - StepF11 0.114849 0.0313 Inf 3.667 0.0131
StepF6 - StepF12 0.220513 0.0313 Inf 7.041 <.0001
StepF7 - StepF8 0.040031 0.0313 Inf 1.278 0.9819
StepF7 - StepF9 0.075231 0.0313 Inf 2.402 0.4044
StepF7 - StepF10 0.117028 0.0313 Inf 3.737 0.0102
StepF7 - StepF11 0.098296 0.0313 Inf 3.138 0.0736
StepF7 - StepF12 0.203960 0.0313 Inf 6.512 <.0001
StepF8 - StepF9 0.035199 0.0313 Inf 1.124 0.9937
StepF8 - StepF10 0.076997 0.0313 Inf 2.458 0.3665
StepF8 - StepF11 0.058264 0.0313 Inf 1.860 0.7839
StepF8 - StepF12 0.163929 0.0313 Inf 5.234 <.0001
StepF9 - StepF10 0.041797 0.0313 Inf 1.335 0.9747
StepF9 - StepF11 0.023065 0.0313 Inf 0.736 0.9999
StepF9 - StepF12 0.128729 0.0313 Inf 4.110 0.0023
StepF10 - StepF11 -0.018732 0.0313 Inf -0.598 1.0000
StepF10 - StepF12 0.086932 0.0313 Inf 2.776 0.1903
StepF11 - StepF12 0.105664 0.0313 Inf 3.374 0.0358
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.101751 0.0313 Inf -3.249 0.0530
StepF1 - StepF3 -0.090757 0.0313 Inf -2.898 0.1415
StepF1 - StepF4 -0.032220 0.0313 Inf -1.029 0.9971
StepF1 - StepF5 0.004576 0.0313 Inf 0.146 1.0000
StepF1 - StepF6 -0.056830 0.0313 Inf -1.815 0.8104
StepF1 - StepF7 -0.040277 0.0313 Inf -1.286 0.9810
StepF1 - StepF8 -0.000245 0.0313 Inf -0.008 1.0000
StepF1 - StepF9 0.034954 0.0313 Inf 1.116 0.9941
StepF1 - StepF10 0.076751 0.0313 Inf 2.451 0.3717
StepF1 - StepF11 0.058019 0.0313 Inf 1.852 0.7885
StepF1 - StepF12 0.163683 0.0313 Inf 5.226 <.0001
StepF2 - StepF3 0.010994 0.0313 Inf 0.351 1.0000
StepF2 - StepF4 0.069531 0.0313 Inf 2.220 0.5348
StepF2 - StepF5 0.106327 0.0313 Inf 3.395 0.0334
StepF2 - StepF6 0.044921 0.0313 Inf 1.434 0.9569
StepF2 - StepF7 0.061474 0.0313 Inf 1.963 0.7189
StepF2 - StepF8 0.101505 0.0313 Inf 3.241 0.0543
StepF2 - StepF9 0.136705 0.0313 Inf 4.365 0.0008
StepF2 - StepF10 0.178502 0.0313 Inf 5.699 <.0001
StepF2 - StepF11 0.159770 0.0313 Inf 5.101 <.0001
StepF2 - StepF12 0.265434 0.0313 Inf 8.475 <.0001
StepF3 - StepF4 0.058537 0.0313 Inf 1.869 0.7787
StepF3 - StepF5 0.095332 0.0313 Inf 3.044 0.0962
StepF3 - StepF6 0.033927 0.0313 Inf 1.083 0.9954
StepF3 - StepF7 0.050480 0.0313 Inf 1.612 0.9053
StepF3 - StepF8 0.090511 0.0313 Inf 2.890 0.1443
StepF3 - StepF9 0.125711 0.0313 Inf 4.014 0.0035
StepF3 - StepF10 0.167508 0.0313 Inf 5.348 <.0001
StepF3 - StepF11 0.148776 0.0313 Inf 4.750 0.0001
StepF3 - StepF12 0.254440 0.0313 Inf 8.124 <.0001
StepF4 - StepF5 0.036796 0.0313 Inf 1.175 0.9908
StepF4 - StepF6 -0.024610 0.0313 Inf -0.786 0.9998
StepF4 - StepF7 -0.008057 0.0313 Inf -0.257 1.0000
StepF4 - StepF8 0.031975 0.0313 Inf 1.021 0.9973
StepF4 - StepF9 0.067174 0.0313 Inf 2.145 0.5901
StepF4 - StepF10 0.108971 0.0313 Inf 3.479 0.0253
StepF4 - StepF11 0.090239 0.0313 Inf 2.881 0.1475
StepF4 - StepF12 0.195903 0.0313 Inf 6.255 <.0001
StepF5 - StepF6 -0.061406 0.0313 Inf -1.961 0.7203
StepF5 - StepF7 -0.044852 0.0313 Inf -1.432 0.9574
StepF5 - StepF8 -0.004821 0.0313 Inf -0.154 1.0000
StepF5 - StepF9 0.030378 0.0313 Inf 0.970 0.9983
StepF5 - StepF10 0.072176 0.0313 Inf 2.305 0.4732
StepF5 - StepF11 0.053443 0.0313 Inf 1.706 0.8658
StepF5 - StepF12 0.159107 0.0313 Inf 5.080 <.0001
StepF6 - StepF7 0.016553 0.0313 Inf 0.529 1.0000
StepF6 - StepF8 0.056584 0.0313 Inf 1.807 0.8148
StepF6 - StepF9 0.091784 0.0313 Inf 2.931 0.1301
StepF6 - StepF10 0.133581 0.0313 Inf 4.265 0.0012
StepF6 - StepF11 0.114849 0.0313 Inf 3.667 0.0131
StepF6 - StepF12 0.220513 0.0313 Inf 7.041 <.0001
StepF7 - StepF8 0.040031 0.0313 Inf 1.278 0.9819
StepF7 - StepF9 0.075231 0.0313 Inf 2.402 0.4044
StepF7 - StepF10 0.117028 0.0313 Inf 3.737 0.0102
StepF7 - StepF11 0.098296 0.0313 Inf 3.138 0.0736
StepF7 - StepF12 0.203960 0.0313 Inf 6.512 <.0001
StepF8 - StepF9 0.035199 0.0313 Inf 1.124 0.9937
StepF8 - StepF10 0.076997 0.0313 Inf 2.458 0.3665
StepF8 - StepF11 0.058264 0.0313 Inf 1.860 0.7839
StepF8 - StepF12 0.163929 0.0313 Inf 5.234 <.0001
StepF9 - StepF10 0.041797 0.0313 Inf 1.335 0.9747
StepF9 - StepF11 0.023065 0.0313 Inf 0.736 0.9999
StepF9 - StepF12 0.128729 0.0313 Inf 4.110 0.0023
StepF10 - StepF11 -0.018732 0.0313 Inf -0.598 1.0000
StepF10 - StepF12 0.086932 0.0313 Inf 2.776 0.1903
StepF11 - StepF12 0.105664 0.0313 Inf 3.374 0.0358
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.1018 0.0313 Inf 3.249 0.0116
StepF3 - StepF2 -0.0110 0.0313 Inf -0.351 1.0000
StepF4 - StepF3 -0.0585 0.0313 Inf -1.869 0.4930
StepF5 - StepF4 -0.0368 0.0313 Inf -1.175 1.0000
StepF6 - StepF5 0.0614 0.0313 Inf 1.961 0.4493
StepF7 - StepF6 -0.0166 0.0313 Inf -0.529 1.0000
StepF8 - StepF7 -0.0400 0.0313 Inf -1.278 1.0000
StepF9 - StepF8 -0.0352 0.0313 Inf -1.124 1.0000
StepF10 - StepF9 -0.0418 0.0313 Inf -1.335 1.0000
StepF11 - StepF10 0.0187 0.0313 Inf 0.598 1.0000
StepF12 - StepF11 -0.1057 0.0313 Inf -3.374 0.0082
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.1018 0.0313 Inf 3.249 0.0116
StepF3 - StepF2 -0.0110 0.0313 Inf -0.351 1.0000
StepF4 - StepF3 -0.0585 0.0313 Inf -1.869 0.4930
StepF5 - StepF4 -0.0368 0.0313 Inf -1.175 1.0000
StepF6 - StepF5 0.0614 0.0313 Inf 1.961 0.4493
StepF7 - StepF6 -0.0166 0.0313 Inf -0.529 1.0000
StepF8 - StepF7 -0.0400 0.0313 Inf -1.278 1.0000
StepF9 - StepF8 -0.0352 0.0313 Inf -1.124 1.0000
StepF10 - StepF9 -0.0418 0.0313 Inf -1.335 1.0000
StepF11 - StepF10 0.0187 0.0313 Inf 0.598 1.0000
StepF12 - StepF11 -0.1057 0.0313 Inf -3.374 0.0082
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests
==============================
TEST | Block 4 | 12 steps | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 202.0651 11 <2e-16 ***
Accuracy 0.0237 1 0.8778
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.694 0.0846 Inf 0.528 0.860
2 0.887 0.0846 Inf 0.721 1.053
3 0.924 0.0846 Inf 0.758 1.090
4 0.781 0.0846 Inf 0.616 0.947
5 0.728 0.0846 Inf 0.562 0.894
6 0.818 0.0846 Inf 0.652 0.983
7 0.782 0.0846 Inf 0.616 0.948
8 0.673 0.0846 Inf 0.507 0.839
9 0.665 0.0846 Inf 0.500 0.831
10 0.702 0.0846 Inf 0.536 0.868
11 0.660 0.0846 Inf 0.495 0.826
12 0.529 0.0846 Inf 0.364 0.695
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.697 0.0834 Inf 0.534 0.861
2 0.890 0.0834 Inf 0.727 1.054
3 0.927 0.0834 Inf 0.764 1.090
4 0.785 0.0834 Inf 0.621 0.948
5 0.731 0.0834 Inf 0.568 0.894
6 0.821 0.0834 Inf 0.657 0.984
7 0.785 0.0834 Inf 0.622 0.949
8 0.676 0.0834 Inf 0.513 0.840
9 0.669 0.0834 Inf 0.505 0.832
10 0.705 0.0834 Inf 0.542 0.869
11 0.664 0.0834 Inf 0.500 0.827
12 0.533 0.0834 Inf 0.369 0.696
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.192878 0.0358 Inf -5.392 <.0001
StepF1 - StepF3 -0.229587 0.0358 Inf -6.419 <.0001
StepF1 - StepF4 -0.087247 0.0358 Inf -2.439 0.3793
StepF1 - StepF5 -0.033545 0.0358 Inf -0.938 0.9987
StepF1 - StepF6 -0.123297 0.0358 Inf -3.447 0.0282
StepF1 - StepF7 -0.087903 0.0358 Inf -2.458 0.3671
StepF1 - StepF8 0.021035 0.0358 Inf 0.588 1.0000
StepF1 - StepF9 0.028954 0.0358 Inf 0.809 0.9997
StepF1 - StepF10 -0.007789 0.0358 Inf -0.218 1.0000
StepF1 - StepF11 0.033889 0.0358 Inf 0.947 0.9986
StepF1 - StepF12 0.164836 0.0358 Inf 4.608 0.0003
StepF2 - StepF3 -0.036710 0.0358 Inf -1.026 0.9971
StepF2 - StepF4 0.105630 0.0358 Inf 2.953 0.1227
StepF2 - StepF5 0.159333 0.0358 Inf 4.454 0.0005
StepF2 - StepF6 0.069581 0.0358 Inf 1.945 0.7305
StepF2 - StepF7 0.104974 0.0358 Inf 2.935 0.1287
StepF2 - StepF8 0.213912 0.0358 Inf 5.980 <.0001
StepF2 - StepF9 0.221832 0.0358 Inf 6.202 <.0001
StepF2 - StepF10 0.185089 0.0358 Inf 5.175 <.0001
StepF2 - StepF11 0.226767 0.0358 Inf 6.340 <.0001
StepF2 - StepF12 0.357714 0.0358 Inf 10.001 <.0001
StepF3 - StepF4 0.142340 0.0358 Inf 3.979 0.0040
StepF3 - StepF5 0.196043 0.0358 Inf 5.481 <.0001
StepF3 - StepF6 0.106291 0.0358 Inf 2.972 0.1169
StepF3 - StepF7 0.141684 0.0358 Inf 3.961 0.0043
StepF3 - StepF8 0.250622 0.0358 Inf 7.007 <.0001
StepF3 - StepF9 0.258542 0.0358 Inf 7.228 <.0001
StepF3 - StepF10 0.221799 0.0358 Inf 6.201 <.0001
StepF3 - StepF11 0.263477 0.0358 Inf 7.366 <.0001
StepF3 - StepF12 0.394424 0.0358 Inf 11.027 <.0001
StepF4 - StepF5 0.053702 0.0358 Inf 1.501 0.9407
StepF4 - StepF6 -0.036049 0.0358 Inf -1.008 0.9976
StepF4 - StepF7 -0.000656 0.0358 Inf -0.018 1.0000
StepF4 - StepF8 0.108282 0.0358 Inf 3.027 0.1007
StepF4 - StepF9 0.116201 0.0358 Inf 3.249 0.0531
StepF4 - StepF10 0.079458 0.0358 Inf 2.221 0.5338
StepF4 - StepF11 0.121136 0.0358 Inf 3.387 0.0343
StepF4 - StepF12 0.252083 0.0358 Inf 7.048 <.0001
StepF5 - StepF6 -0.089752 0.0358 Inf -2.509 0.3339
StepF5 - StepF7 -0.054358 0.0358 Inf -1.520 0.9355
StepF5 - StepF8 0.054579 0.0358 Inf 1.526 0.9338
StepF5 - StepF9 0.062499 0.0358 Inf 1.747 0.8461
StepF5 - StepF10 0.025756 0.0358 Inf 0.720 0.9999
StepF5 - StepF11 0.067434 0.0358 Inf 1.885 0.7687
StepF5 - StepF12 0.198381 0.0358 Inf 5.546 <.0001
StepF6 - StepF7 0.035394 0.0358 Inf 0.990 0.9979
StepF6 - StepF8 0.144331 0.0358 Inf 4.035 0.0032
StepF6 - StepF9 0.152251 0.0358 Inf 4.257 0.0013
StepF6 - StepF10 0.115508 0.0358 Inf 3.229 0.0563
StepF6 - StepF11 0.157186 0.0358 Inf 4.394 0.0007
StepF6 - StepF12 0.288133 0.0358 Inf 8.055 <.0001
StepF7 - StepF8 0.108938 0.0358 Inf 3.046 0.0957
StepF7 - StepF9 0.116857 0.0358 Inf 3.267 0.0502
StepF7 - StepF10 0.080114 0.0358 Inf 2.240 0.5204
StepF7 - StepF11 0.121792 0.0358 Inf 3.405 0.0324
StepF7 - StepF12 0.252739 0.0358 Inf 7.066 <.0001
StepF8 - StepF9 0.007920 0.0358 Inf 0.221 1.0000
StepF8 - StepF10 -0.028823 0.0358 Inf -0.806 0.9997
StepF8 - StepF11 0.012855 0.0358 Inf 0.359 1.0000
StepF8 - StepF12 0.143802 0.0358 Inf 4.020 0.0034
StepF9 - StepF10 -0.036743 0.0358 Inf -1.027 0.9971
StepF9 - StepF11 0.004935 0.0358 Inf 0.138 1.0000
StepF9 - StepF12 0.135882 0.0358 Inf 3.799 0.0080
StepF10 - StepF11 0.041678 0.0358 Inf 1.165 0.9914
StepF10 - StepF12 0.172625 0.0358 Inf 4.826 0.0001
StepF11 - StepF12 0.130947 0.0358 Inf 3.661 0.0134
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.192878 0.0358 Inf -5.392 <.0001
StepF1 - StepF3 -0.229587 0.0358 Inf -6.419 <.0001
StepF1 - StepF4 -0.087247 0.0358 Inf -2.439 0.3793
StepF1 - StepF5 -0.033545 0.0358 Inf -0.938 0.9987
StepF1 - StepF6 -0.123297 0.0358 Inf -3.447 0.0282
StepF1 - StepF7 -0.087903 0.0358 Inf -2.458 0.3671
StepF1 - StepF8 0.021035 0.0358 Inf 0.588 1.0000
StepF1 - StepF9 0.028954 0.0358 Inf 0.809 0.9997
StepF1 - StepF10 -0.007789 0.0358 Inf -0.218 1.0000
StepF1 - StepF11 0.033889 0.0358 Inf 0.947 0.9986
StepF1 - StepF12 0.164836 0.0358 Inf 4.608 0.0003
StepF2 - StepF3 -0.036710 0.0358 Inf -1.026 0.9971
StepF2 - StepF4 0.105630 0.0358 Inf 2.953 0.1227
StepF2 - StepF5 0.159333 0.0358 Inf 4.454 0.0005
StepF2 - StepF6 0.069581 0.0358 Inf 1.945 0.7305
StepF2 - StepF7 0.104974 0.0358 Inf 2.935 0.1287
StepF2 - StepF8 0.213912 0.0358 Inf 5.980 <.0001
StepF2 - StepF9 0.221832 0.0358 Inf 6.202 <.0001
StepF2 - StepF10 0.185089 0.0358 Inf 5.175 <.0001
StepF2 - StepF11 0.226767 0.0358 Inf 6.340 <.0001
StepF2 - StepF12 0.357714 0.0358 Inf 10.001 <.0001
StepF3 - StepF4 0.142340 0.0358 Inf 3.979 0.0040
StepF3 - StepF5 0.196043 0.0358 Inf 5.481 <.0001
StepF3 - StepF6 0.106291 0.0358 Inf 2.972 0.1169
StepF3 - StepF7 0.141684 0.0358 Inf 3.961 0.0043
StepF3 - StepF8 0.250622 0.0358 Inf 7.007 <.0001
StepF3 - StepF9 0.258542 0.0358 Inf 7.228 <.0001
StepF3 - StepF10 0.221799 0.0358 Inf 6.201 <.0001
StepF3 - StepF11 0.263477 0.0358 Inf 7.366 <.0001
StepF3 - StepF12 0.394424 0.0358 Inf 11.027 <.0001
StepF4 - StepF5 0.053702 0.0358 Inf 1.501 0.9407
StepF4 - StepF6 -0.036049 0.0358 Inf -1.008 0.9976
StepF4 - StepF7 -0.000656 0.0358 Inf -0.018 1.0000
StepF4 - StepF8 0.108282 0.0358 Inf 3.027 0.1007
StepF4 - StepF9 0.116201 0.0358 Inf 3.249 0.0531
StepF4 - StepF10 0.079458 0.0358 Inf 2.221 0.5338
StepF4 - StepF11 0.121136 0.0358 Inf 3.387 0.0343
StepF4 - StepF12 0.252083 0.0358 Inf 7.048 <.0001
StepF5 - StepF6 -0.089752 0.0358 Inf -2.509 0.3339
StepF5 - StepF7 -0.054358 0.0358 Inf -1.520 0.9355
StepF5 - StepF8 0.054579 0.0358 Inf 1.526 0.9338
StepF5 - StepF9 0.062499 0.0358 Inf 1.747 0.8461
StepF5 - StepF10 0.025756 0.0358 Inf 0.720 0.9999
StepF5 - StepF11 0.067434 0.0358 Inf 1.885 0.7687
StepF5 - StepF12 0.198381 0.0358 Inf 5.546 <.0001
StepF6 - StepF7 0.035394 0.0358 Inf 0.990 0.9979
StepF6 - StepF8 0.144331 0.0358 Inf 4.035 0.0032
StepF6 - StepF9 0.152251 0.0358 Inf 4.257 0.0013
StepF6 - StepF10 0.115508 0.0358 Inf 3.229 0.0563
StepF6 - StepF11 0.157186 0.0358 Inf 4.394 0.0007
StepF6 - StepF12 0.288133 0.0358 Inf 8.055 <.0001
StepF7 - StepF8 0.108938 0.0358 Inf 3.046 0.0957
StepF7 - StepF9 0.116857 0.0358 Inf 3.267 0.0502
StepF7 - StepF10 0.080114 0.0358 Inf 2.240 0.5204
StepF7 - StepF11 0.121792 0.0358 Inf 3.405 0.0324
StepF7 - StepF12 0.252739 0.0358 Inf 7.066 <.0001
StepF8 - StepF9 0.007920 0.0358 Inf 0.221 1.0000
StepF8 - StepF10 -0.028823 0.0358 Inf -0.806 0.9997
StepF8 - StepF11 0.012855 0.0358 Inf 0.359 1.0000
StepF8 - StepF12 0.143802 0.0358 Inf 4.020 0.0034
StepF9 - StepF10 -0.036743 0.0358 Inf -1.027 0.9971
StepF9 - StepF11 0.004935 0.0358 Inf 0.138 1.0000
StepF9 - StepF12 0.135882 0.0358 Inf 3.799 0.0080
StepF10 - StepF11 0.041678 0.0358 Inf 1.165 0.9914
StepF10 - StepF12 0.172625 0.0358 Inf 4.826 0.0001
StepF11 - StepF12 0.130947 0.0358 Inf 3.661 0.0134
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.19288 0.0358 Inf 5.392 <.0001
StepF3 - StepF2 0.03671 0.0358 Inf 1.026 1.0000
StepF4 - StepF3 -0.14234 0.0358 Inf -3.979 0.0007
StepF5 - StepF4 -0.05370 0.0358 Inf -1.501 0.7996
StepF6 - StepF5 0.08975 0.0358 Inf 2.509 0.0847
StepF7 - StepF6 -0.03539 0.0358 Inf -0.990 1.0000
StepF8 - StepF7 -0.10894 0.0358 Inf -3.046 0.0186
StepF9 - StepF8 -0.00792 0.0358 Inf -0.221 1.0000
StepF10 - StepF9 0.03674 0.0358 Inf 1.027 1.0000
StepF11 - StepF10 -0.04168 0.0358 Inf -1.165 1.0000
StepF12 - StepF11 -0.13095 0.0358 Inf -3.661 0.0023
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.19288 0.0358 Inf 5.392 <.0001
StepF3 - StepF2 0.03671 0.0358 Inf 1.026 1.0000
StepF4 - StepF3 -0.14234 0.0358 Inf -3.979 0.0007
StepF5 - StepF4 -0.05370 0.0358 Inf -1.501 0.7996
StepF6 - StepF5 0.08975 0.0358 Inf 2.509 0.0847
StepF7 - StepF6 -0.03539 0.0358 Inf -0.990 1.0000
StepF8 - StepF7 -0.10894 0.0358 Inf -3.046 0.0186
StepF9 - StepF8 -0.00792 0.0358 Inf -0.221 1.0000
StepF10 - StepF9 0.03674 0.0358 Inf 1.027 1.0000
StepF11 - StepF10 -0.04168 0.0358 Inf -1.165 1.0000
StepF12 - StepF11 -0.13095 0.0358 Inf -3.661 0.0023
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests
==============================
TEST | Block 4 | 12 steps | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 201.1109 11 <2e-16 ***
Accuracy 0.0973 1 0.7551
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.45 0.149 Inf 1.156 1.74
2 1.70 0.149 Inf 1.411 2.00
3 1.75 0.149 Inf 1.455 2.04
4 1.60 0.149 Inf 1.310 1.90
5 1.45 0.149 Inf 1.153 1.74
6 1.48 0.149 Inf 1.184 1.77
7 1.52 0.149 Inf 1.228 1.81
8 1.38 0.149 Inf 1.089 1.67
9 1.28 0.149 Inf 0.985 1.57
10 1.32 0.149 Inf 1.029 1.61
11 1.34 0.149 Inf 1.050 1.64
12 1.10 0.149 Inf 0.812 1.40
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.46 0.147 Inf 1.171 1.75
2 1.72 0.147 Inf 1.426 2.00
3 1.76 0.147 Inf 1.470 2.05
4 1.61 0.147 Inf 1.325 1.90
5 1.46 0.147 Inf 1.168 1.75
6 1.49 0.147 Inf 1.199 1.78
7 1.53 0.147 Inf 1.244 1.82
8 1.39 0.147 Inf 1.104 1.68
9 1.29 0.147 Inf 1.001 1.58
10 1.33 0.147 Inf 1.044 1.62
11 1.35 0.147 Inf 1.066 1.64
12 1.12 0.147 Inf 0.827 1.41
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.25512 0.0601 Inf -4.245 0.0013
StepF1 - StepF3 -0.29878 0.0601 Inf -4.972 <.0001
StepF1 - StepF4 -0.15367 0.0601 Inf -2.557 0.3044
StepF1 - StepF5 0.00315 0.0601 Inf 0.052 1.0000
StepF1 - StepF6 -0.02816 0.0601 Inf -0.469 1.0000
StepF1 - StepF7 -0.07240 0.0601 Inf -1.205 0.9887
StepF1 - StepF8 0.06690 0.0601 Inf 1.113 0.9942
StepF1 - StepF9 0.17049 0.0601 Inf 2.837 0.1644
StepF1 - StepF10 0.12721 0.0601 Inf 2.117 0.6105
StepF1 - StepF11 0.10566 0.0601 Inf 1.758 0.8406
StepF1 - StepF12 0.34383 0.0601 Inf 5.722 <.0001
StepF2 - StepF3 -0.04366 0.0601 Inf -0.727 0.9999
StepF2 - StepF4 0.10145 0.0601 Inf 1.688 0.8740
StepF2 - StepF5 0.25827 0.0601 Inf 4.298 0.0010
StepF2 - StepF6 0.22696 0.0601 Inf 3.777 0.0087
StepF2 - StepF7 0.18272 0.0601 Inf 3.041 0.0971
StepF2 - StepF8 0.32201 0.0601 Inf 5.359 <.0001
StepF2 - StepF9 0.42560 0.0601 Inf 7.082 <.0001
StepF2 - StepF10 0.38233 0.0601 Inf 6.362 <.0001
StepF2 - StepF11 0.36077 0.0601 Inf 6.004 <.0001
StepF2 - StepF12 0.59895 0.0601 Inf 9.967 <.0001
StepF3 - StepF4 0.14511 0.0601 Inf 2.415 0.3957
StepF3 - StepF5 0.30193 0.0601 Inf 5.025 <.0001
StepF3 - StepF6 0.27062 0.0601 Inf 4.503 0.0004
StepF3 - StepF7 0.22638 0.0601 Inf 3.767 0.0091
StepF3 - StepF8 0.36568 0.0601 Inf 6.085 <.0001
StepF3 - StepF9 0.46927 0.0601 Inf 7.809 <.0001
StepF3 - StepF10 0.42600 0.0601 Inf 7.089 <.0001
StepF3 - StepF11 0.40444 0.0601 Inf 6.730 <.0001
StepF3 - StepF12 0.64261 0.0601 Inf 10.694 <.0001
StepF4 - StepF5 0.15682 0.0601 Inf 2.610 0.2740
StepF4 - StepF6 0.12551 0.0601 Inf 2.089 0.6311
StepF4 - StepF7 0.08127 0.0601 Inf 1.352 0.9720
StepF4 - StepF8 0.22057 0.0601 Inf 3.670 0.0129
StepF4 - StepF9 0.32415 0.0601 Inf 5.394 <.0001
StepF4 - StepF10 0.28088 0.0601 Inf 4.674 0.0002
StepF4 - StepF11 0.25932 0.0601 Inf 4.315 0.0010
StepF4 - StepF12 0.49750 0.0601 Inf 8.279 <.0001
StepF5 - StepF6 -0.03131 0.0601 Inf -0.521 1.0000
StepF5 - StepF7 -0.07555 0.0601 Inf -1.257 0.9841
StepF5 - StepF8 0.06375 0.0601 Inf 1.061 0.9962
StepF5 - StepF9 0.16733 0.0601 Inf 2.785 0.1864
StepF5 - StepF10 0.12406 0.0601 Inf 2.065 0.6484
StepF5 - StepF11 0.10250 0.0601 Inf 1.706 0.8661
StepF5 - StepF12 0.34068 0.0601 Inf 5.669 <.0001
StepF6 - StepF7 -0.04424 0.0601 Inf -0.736 0.9999
StepF6 - StepF8 0.09506 0.0601 Inf 1.582 0.9160
StepF6 - StepF9 0.19865 0.0601 Inf 3.306 0.0445
StepF6 - StepF10 0.15537 0.0601 Inf 2.586 0.2877
StepF6 - StepF11 0.13382 0.0601 Inf 2.227 0.5298
StepF6 - StepF12 0.37199 0.0601 Inf 6.190 <.0001
StepF7 - StepF8 0.13930 0.0601 Inf 2.318 0.4635
StepF7 - StepF9 0.24289 0.0601 Inf 4.042 0.0031
StepF7 - StepF10 0.19961 0.0601 Inf 3.322 0.0423
StepF7 - StepF11 0.17806 0.0601 Inf 2.963 0.1196
StepF7 - StepF12 0.41623 0.0601 Inf 6.927 <.0001
StepF8 - StepF9 0.10359 0.0601 Inf 1.724 0.8576
StepF8 - StepF10 0.06032 0.0601 Inf 1.004 0.9977
StepF8 - StepF11 0.03876 0.0601 Inf 0.645 1.0000
StepF8 - StepF12 0.27693 0.0601 Inf 4.608 0.0003
StepF9 - StepF10 -0.04327 0.0601 Inf -0.720 0.9999
StepF9 - StepF11 -0.06483 0.0601 Inf -1.079 0.9956
StepF9 - StepF12 0.17335 0.0601 Inf 2.885 0.1462
StepF10 - StepF11 -0.02156 0.0601 Inf -0.359 1.0000
StepF10 - StepF12 0.21662 0.0601 Inf 3.605 0.0164
StepF11 - StepF12 0.23818 0.0601 Inf 3.963 0.0042
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.25512 0.0601 Inf -4.245 0.0013
StepF1 - StepF3 -0.29878 0.0601 Inf -4.972 <.0001
StepF1 - StepF4 -0.15367 0.0601 Inf -2.557 0.3044
StepF1 - StepF5 0.00315 0.0601 Inf 0.052 1.0000
StepF1 - StepF6 -0.02816 0.0601 Inf -0.469 1.0000
StepF1 - StepF7 -0.07240 0.0601 Inf -1.205 0.9887
StepF1 - StepF8 0.06690 0.0601 Inf 1.113 0.9942
StepF1 - StepF9 0.17049 0.0601 Inf 2.837 0.1644
StepF1 - StepF10 0.12721 0.0601 Inf 2.117 0.6105
StepF1 - StepF11 0.10566 0.0601 Inf 1.758 0.8406
StepF1 - StepF12 0.34383 0.0601 Inf 5.722 <.0001
StepF2 - StepF3 -0.04366 0.0601 Inf -0.727 0.9999
StepF2 - StepF4 0.10145 0.0601 Inf 1.688 0.8740
StepF2 - StepF5 0.25827 0.0601 Inf 4.298 0.0010
StepF2 - StepF6 0.22696 0.0601 Inf 3.777 0.0087
StepF2 - StepF7 0.18272 0.0601 Inf 3.041 0.0971
StepF2 - StepF8 0.32201 0.0601 Inf 5.359 <.0001
StepF2 - StepF9 0.42560 0.0601 Inf 7.082 <.0001
StepF2 - StepF10 0.38233 0.0601 Inf 6.362 <.0001
StepF2 - StepF11 0.36077 0.0601 Inf 6.004 <.0001
StepF2 - StepF12 0.59895 0.0601 Inf 9.967 <.0001
StepF3 - StepF4 0.14511 0.0601 Inf 2.415 0.3957
StepF3 - StepF5 0.30193 0.0601 Inf 5.025 <.0001
StepF3 - StepF6 0.27062 0.0601 Inf 4.503 0.0004
StepF3 - StepF7 0.22638 0.0601 Inf 3.767 0.0091
StepF3 - StepF8 0.36568 0.0601 Inf 6.085 <.0001
StepF3 - StepF9 0.46927 0.0601 Inf 7.809 <.0001
StepF3 - StepF10 0.42600 0.0601 Inf 7.089 <.0001
StepF3 - StepF11 0.40444 0.0601 Inf 6.730 <.0001
StepF3 - StepF12 0.64261 0.0601 Inf 10.694 <.0001
StepF4 - StepF5 0.15682 0.0601 Inf 2.610 0.2740
StepF4 - StepF6 0.12551 0.0601 Inf 2.089 0.6311
StepF4 - StepF7 0.08127 0.0601 Inf 1.352 0.9720
StepF4 - StepF8 0.22057 0.0601 Inf 3.670 0.0129
StepF4 - StepF9 0.32415 0.0601 Inf 5.394 <.0001
StepF4 - StepF10 0.28088 0.0601 Inf 4.674 0.0002
StepF4 - StepF11 0.25932 0.0601 Inf 4.315 0.0010
StepF4 - StepF12 0.49750 0.0601 Inf 8.279 <.0001
StepF5 - StepF6 -0.03131 0.0601 Inf -0.521 1.0000
StepF5 - StepF7 -0.07555 0.0601 Inf -1.257 0.9841
StepF5 - StepF8 0.06375 0.0601 Inf 1.061 0.9962
StepF5 - StepF9 0.16733 0.0601 Inf 2.785 0.1864
StepF5 - StepF10 0.12406 0.0601 Inf 2.065 0.6484
StepF5 - StepF11 0.10250 0.0601 Inf 1.706 0.8661
StepF5 - StepF12 0.34068 0.0601 Inf 5.669 <.0001
StepF6 - StepF7 -0.04424 0.0601 Inf -0.736 0.9999
StepF6 - StepF8 0.09506 0.0601 Inf 1.582 0.9160
StepF6 - StepF9 0.19865 0.0601 Inf 3.306 0.0445
StepF6 - StepF10 0.15537 0.0601 Inf 2.586 0.2877
StepF6 - StepF11 0.13382 0.0601 Inf 2.227 0.5298
StepF6 - StepF12 0.37199 0.0601 Inf 6.190 <.0001
StepF7 - StepF8 0.13930 0.0601 Inf 2.318 0.4635
StepF7 - StepF9 0.24289 0.0601 Inf 4.042 0.0031
StepF7 - StepF10 0.19961 0.0601 Inf 3.322 0.0423
StepF7 - StepF11 0.17806 0.0601 Inf 2.963 0.1196
StepF7 - StepF12 0.41623 0.0601 Inf 6.927 <.0001
StepF8 - StepF9 0.10359 0.0601 Inf 1.724 0.8576
StepF8 - StepF10 0.06032 0.0601 Inf 1.004 0.9977
StepF8 - StepF11 0.03876 0.0601 Inf 0.645 1.0000
StepF8 - StepF12 0.27693 0.0601 Inf 4.608 0.0003
StepF9 - StepF10 -0.04327 0.0601 Inf -0.720 0.9999
StepF9 - StepF11 -0.06483 0.0601 Inf -1.079 0.9956
StepF9 - StepF12 0.17335 0.0601 Inf 2.885 0.1462
StepF10 - StepF11 -0.02156 0.0601 Inf -0.359 1.0000
StepF10 - StepF12 0.21662 0.0601 Inf 3.605 0.0164
StepF11 - StepF12 0.23818 0.0601 Inf 3.963 0.0042
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2551 0.0601 Inf 4.245 0.0002
StepF3 - StepF2 0.0437 0.0601 Inf 0.727 1.0000
StepF4 - StepF3 -0.1451 0.0601 Inf -2.415 0.1259
StepF5 - StepF4 -0.1568 0.0601 Inf -2.610 0.0816
StepF6 - StepF5 0.0313 0.0601 Inf 0.521 1.0000
StepF7 - StepF6 0.0442 0.0601 Inf 0.736 1.0000
StepF8 - StepF7 -0.1393 0.0601 Inf -2.318 0.1431
StepF9 - StepF8 -0.1036 0.0601 Inf -1.724 0.5084
StepF10 - StepF9 0.0433 0.0601 Inf 0.720 1.0000
StepF11 - StepF10 0.0216 0.0601 Inf 0.359 1.0000
StepF12 - StepF11 -0.2382 0.0601 Inf -3.963 0.0007
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2551 0.0601 Inf 4.245 0.0002
StepF3 - StepF2 0.0437 0.0601 Inf 0.727 1.0000
StepF4 - StepF3 -0.1451 0.0601 Inf -2.415 0.1259
StepF5 - StepF4 -0.1568 0.0601 Inf -2.610 0.0816
StepF6 - StepF5 0.0313 0.0601 Inf 0.521 1.0000
StepF7 - StepF6 0.0442 0.0601 Inf 0.736 1.0000
StepF8 - StepF7 -0.1393 0.0601 Inf -2.318 0.1431
StepF9 - StepF8 -0.1036 0.0601 Inf -1.724 0.5084
StepF10 - StepF9 0.0433 0.0601 Inf 0.720 1.0000
StepF11 - StepF10 0.0216 0.0601 Inf 0.359 1.0000
StepF12 - StepF11 -0.2382 0.0601 Inf -3.963 0.0007
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests .report_step_test(sw_b4_18, "4", "18 steps")
==============================
TEST | Block 4 | 18 steps | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 223.7951 17 <2e-16 ***
Accuracy 0.0416 1 0.8384
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.699 0.0720 Inf 0.558 0.840
2 0.814 0.0720 Inf 0.673 0.955
3 0.783 0.0720 Inf 0.642 0.924
4 0.756 0.0720 Inf 0.615 0.898
5 0.700 0.0720 Inf 0.558 0.841
6 0.839 0.0720 Inf 0.697 0.980
7 0.710 0.0720 Inf 0.569 0.851
8 0.701 0.0720 Inf 0.559 0.842
9 0.746 0.0720 Inf 0.605 0.887
10 0.659 0.0720 Inf 0.518 0.801
11 0.685 0.0720 Inf 0.544 0.826
12 0.605 0.0720 Inf 0.464 0.746
13 0.655 0.0720 Inf 0.514 0.796
14 0.661 0.0720 Inf 0.520 0.802
15 0.687 0.0720 Inf 0.546 0.829
16 0.654 0.0720 Inf 0.513 0.795
17 0.548 0.0720 Inf 0.407 0.689
18 0.521 0.0720 Inf 0.380 0.662
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.696 0.0714 Inf 0.556 0.836
2 0.811 0.0714 Inf 0.671 0.951
3 0.780 0.0714 Inf 0.640 0.920
4 0.753 0.0714 Inf 0.613 0.893
5 0.696 0.0714 Inf 0.556 0.836
6 0.835 0.0714 Inf 0.695 0.975
7 0.707 0.0714 Inf 0.567 0.847
8 0.697 0.0714 Inf 0.558 0.837
9 0.743 0.0714 Inf 0.603 0.883
10 0.656 0.0714 Inf 0.516 0.796
11 0.682 0.0714 Inf 0.542 0.822
12 0.602 0.0714 Inf 0.462 0.742
13 0.652 0.0714 Inf 0.512 0.792
14 0.658 0.0714 Inf 0.518 0.798
15 0.684 0.0714 Inf 0.544 0.824
16 0.651 0.0714 Inf 0.511 0.791
17 0.545 0.0714 Inf 0.405 0.685
18 0.518 0.0714 Inf 0.378 0.658
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.115213 0.032 Inf -3.599 0.0347
StepF1 - StepF3 -0.084028 0.032 Inf -2.625 0.4346
StepF1 - StepF4 -0.057319 0.032 Inf -1.791 0.9469
StepF1 - StepF5 -0.000365 0.032 Inf -0.011 1.0000
StepF1 - StepF6 -0.139372 0.032 Inf -4.354 0.0018
StepF1 - StepF7 -0.010956 0.032 Inf -0.342 1.0000
StepF1 - StepF8 -0.001450 0.032 Inf -0.045 1.0000
StepF1 - StepF9 -0.046816 0.032 Inf -1.463 0.9930
StepF1 - StepF10 0.039705 0.032 Inf 1.240 0.9990
StepF1 - StepF11 0.014342 0.032 Inf 0.448 1.0000
StepF1 - StepF12 0.094244 0.032 Inf 2.944 0.2281
StepF1 - StepF13 0.044322 0.032 Inf 1.385 0.9963
StepF1 - StepF14 0.038434 0.032 Inf 1.201 0.9994
StepF1 - StepF15 0.011701 0.032 Inf 0.366 1.0000
StepF1 - StepF16 0.045237 0.032 Inf 1.413 0.9953
StepF1 - StepF17 0.150937 0.032 Inf 4.715 0.0003
StepF1 - StepF18 0.177955 0.032 Inf 5.559 <.0001
StepF2 - StepF3 0.031185 0.032 Inf 0.974 1.0000
StepF2 - StepF4 0.057894 0.032 Inf 1.809 0.9420
StepF2 - StepF5 0.114848 0.032 Inf 3.588 0.0360
StepF2 - StepF6 -0.024159 0.032 Inf -0.755 1.0000
StepF2 - StepF7 0.104257 0.032 Inf 3.257 0.1013
StepF2 - StepF8 0.113763 0.032 Inf 3.554 0.0404
StepF2 - StepF9 0.068397 0.032 Inf 2.137 0.7947
StepF2 - StepF10 0.154918 0.032 Inf 4.840 0.0002
StepF2 - StepF11 0.129555 0.032 Inf 4.047 0.0066
StepF2 - StepF12 0.209457 0.032 Inf 6.544 <.0001
StepF2 - StepF13 0.159534 0.032 Inf 4.984 0.0001
StepF2 - StepF14 0.153647 0.032 Inf 4.800 0.0002
StepF2 - StepF15 0.126914 0.032 Inf 3.965 0.0091
StepF2 - StepF16 0.160450 0.032 Inf 5.013 0.0001
StepF2 - StepF17 0.266149 0.032 Inf 8.315 <.0001
StepF2 - StepF18 0.293168 0.032 Inf 9.159 <.0001
StepF3 - StepF4 0.026710 0.032 Inf 0.834 1.0000
StepF3 - StepF5 0.083663 0.032 Inf 2.614 0.4431
StepF3 - StepF6 -0.055344 0.032 Inf -1.729 0.9613
StepF3 - StepF7 0.073072 0.032 Inf 2.283 0.6961
StepF3 - StepF8 0.082578 0.032 Inf 2.580 0.4687
StepF3 - StepF9 0.037212 0.032 Inf 1.163 0.9996
StepF3 - StepF10 0.123734 0.032 Inf 3.866 0.0134
StepF3 - StepF11 0.098371 0.032 Inf 3.073 0.1666
StepF3 - StepF12 0.178272 0.032 Inf 5.569 <.0001
StepF3 - StepF13 0.128350 0.032 Inf 4.010 0.0077
StepF3 - StepF14 0.122463 0.032 Inf 3.826 0.0155
StepF3 - StepF15 0.095729 0.032 Inf 2.991 0.2044
StepF3 - StepF16 0.129266 0.032 Inf 4.038 0.0068
StepF3 - StepF17 0.234965 0.032 Inf 7.340 <.0001
StepF3 - StepF18 0.261984 0.032 Inf 8.185 <.0001
StepF4 - StepF5 0.056953 0.032 Inf 1.779 0.9498
StepF4 - StepF6 -0.082054 0.032 Inf -2.563 0.4812
StepF4 - StepF7 0.046363 0.032 Inf 1.448 0.9937
StepF4 - StepF8 0.055868 0.032 Inf 1.745 0.9578
StepF4 - StepF9 0.010502 0.032 Inf 0.328 1.0000
StepF4 - StepF10 0.097024 0.032 Inf 3.031 0.1852
StepF4 - StepF11 0.071661 0.032 Inf 2.239 0.7275
StepF4 - StepF12 0.151562 0.032 Inf 4.735 0.0003
StepF4 - StepF13 0.101640 0.032 Inf 3.175 0.1273
StepF4 - StepF14 0.095753 0.032 Inf 2.991 0.2040
StepF4 - StepF15 0.069020 0.032 Inf 2.156 0.7826
StepF4 - StepF16 0.102556 0.032 Inf 3.204 0.1176
StepF4 - StepF17 0.208255 0.032 Inf 6.506 <.0001
StepF4 - StepF18 0.235274 0.032 Inf 7.350 <.0001
StepF5 - StepF6 -0.139007 0.032 Inf -4.343 0.0019
StepF5 - StepF7 -0.010591 0.032 Inf -0.331 1.0000
StepF5 - StepF8 -0.001085 0.032 Inf -0.034 1.0000
StepF5 - StepF9 -0.046451 0.032 Inf -1.451 0.9936
StepF5 - StepF10 0.040071 0.032 Inf 1.252 0.9989
StepF5 - StepF11 0.014708 0.032 Inf 0.459 1.0000
StepF5 - StepF12 0.094609 0.032 Inf 2.956 0.2221
StepF5 - StepF13 0.044687 0.032 Inf 1.396 0.9959
StepF5 - StepF14 0.038800 0.032 Inf 1.212 0.9993
StepF5 - StepF15 0.012066 0.032 Inf 0.377 1.0000
StepF5 - StepF16 0.045602 0.032 Inf 1.425 0.9948
StepF5 - StepF17 0.151302 0.032 Inf 4.727 0.0003
StepF5 - StepF18 0.178321 0.032 Inf 5.571 <.0001
StepF6 - StepF7 0.128416 0.032 Inf 4.012 0.0076
StepF6 - StepF8 0.137922 0.032 Inf 4.309 0.0022
StepF6 - StepF9 0.092556 0.032 Inf 2.892 0.2571
StepF6 - StepF10 0.179077 0.032 Inf 5.595 <.0001
StepF6 - StepF11 0.153715 0.032 Inf 4.802 0.0002
StepF6 - StepF12 0.233616 0.032 Inf 7.298 <.0001
StepF6 - StepF13 0.183694 0.032 Inf 5.739 <.0001
StepF6 - StepF14 0.177807 0.032 Inf 5.555 <.0001
StepF6 - StepF15 0.151073 0.032 Inf 4.720 0.0003
StepF6 - StepF16 0.184609 0.032 Inf 5.767 <.0001
StepF6 - StepF17 0.290309 0.032 Inf 9.069 <.0001
StepF6 - StepF18 0.317328 0.032 Inf 9.914 <.0001
StepF7 - StepF8 0.009506 0.032 Inf 0.297 1.0000
StepF7 - StepF9 -0.035860 0.032 Inf -1.120 0.9997
StepF7 - StepF10 0.050661 0.032 Inf 1.583 0.9837
StepF7 - StepF11 0.025298 0.032 Inf 0.790 1.0000
StepF7 - StepF12 0.105200 0.032 Inf 3.287 0.0930
StepF7 - StepF13 0.055278 0.032 Inf 1.727 0.9617
StepF7 - StepF14 0.049390 0.032 Inf 1.543 0.9875
StepF7 - StepF15 0.022657 0.032 Inf 0.708 1.0000
StepF7 - StepF16 0.056193 0.032 Inf 1.756 0.9555
StepF7 - StepF17 0.161893 0.032 Inf 5.058 0.0001
StepF7 - StepF18 0.188912 0.032 Inf 5.902 <.0001
StepF8 - StepF9 -0.045366 0.032 Inf -1.417 0.9951
StepF8 - StepF10 0.041155 0.032 Inf 1.286 0.9985
StepF8 - StepF11 0.015793 0.032 Inf 0.493 1.0000
StepF8 - StepF12 0.095694 0.032 Inf 2.990 0.2049
StepF8 - StepF13 0.045772 0.032 Inf 1.430 0.9946
StepF8 - StepF14 0.039885 0.032 Inf 1.246 0.9990
StepF8 - StepF15 0.013151 0.032 Inf 0.411 1.0000
StepF8 - StepF16 0.046687 0.032 Inf 1.459 0.9932
StepF8 - StepF17 0.152387 0.032 Inf 4.761 0.0003
StepF8 - StepF18 0.179406 0.032 Inf 5.605 <.0001
StepF9 - StepF10 0.086521 0.032 Inf 2.703 0.3781
StepF9 - StepF11 0.061158 0.032 Inf 1.911 0.9083
StepF9 - StepF12 0.141060 0.032 Inf 4.407 0.0014
StepF9 - StepF13 0.091138 0.032 Inf 2.847 0.2832
StepF9 - StepF14 0.085250 0.032 Inf 2.663 0.4065
StepF9 - StepF15 0.058517 0.032 Inf 1.828 0.9364
StepF9 - StepF16 0.092053 0.032 Inf 2.876 0.2662
StepF9 - StepF17 0.197753 0.032 Inf 6.178 <.0001
StepF9 - StepF18 0.224772 0.032 Inf 7.022 <.0001
StepF10 - StepF11 -0.025363 0.032 Inf -0.792 1.0000
StepF10 - StepF12 0.054538 0.032 Inf 1.704 0.9663
StepF10 - StepF13 0.004616 0.032 Inf 0.144 1.0000
StepF10 - StepF14 -0.001271 0.032 Inf -0.040 1.0000
StepF10 - StepF15 -0.028004 0.032 Inf -0.875 1.0000
StepF10 - StepF16 0.005532 0.032 Inf 0.173 1.0000
StepF10 - StepF17 0.111231 0.032 Inf 3.475 0.0523
StepF10 - StepF18 0.138250 0.032 Inf 4.319 0.0021
StepF11 - StepF12 0.079901 0.032 Inf 2.496 0.5332
StepF11 - StepF13 0.029979 0.032 Inf 0.937 1.0000
StepF11 - StepF14 0.024092 0.032 Inf 0.753 1.0000
StepF11 - StepF15 -0.002641 0.032 Inf -0.083 1.0000
StepF11 - StepF16 0.030895 0.032 Inf 0.965 1.0000
StepF11 - StepF17 0.136594 0.032 Inf 4.267 0.0026
StepF11 - StepF18 0.163613 0.032 Inf 5.111 <.0001
StepF12 - StepF13 -0.049922 0.032 Inf -1.560 0.9860
StepF12 - StepF14 -0.055809 0.032 Inf -1.744 0.9582
StepF12 - StepF15 -0.082543 0.032 Inf -2.579 0.4696
StepF12 - StepF16 -0.049006 0.032 Inf -1.531 0.9885
StepF12 - StepF17 0.056693 0.032 Inf 1.771 0.9518
StepF12 - StepF18 0.083712 0.032 Inf 2.615 0.4420
StepF13 - StepF14 -0.005887 0.032 Inf -0.184 1.0000
StepF13 - StepF15 -0.032620 0.032 Inf -1.019 0.9999
StepF13 - StepF16 0.000916 0.032 Inf 0.029 1.0000
StepF13 - StepF17 0.106615 0.032 Inf 3.331 0.0817
StepF13 - StepF18 0.133634 0.032 Inf 4.175 0.0039
StepF14 - StepF15 -0.026733 0.032 Inf -0.835 1.0000
StepF14 - StepF16 0.006803 0.032 Inf 0.213 1.0000
StepF14 - StepF17 0.112502 0.032 Inf 3.515 0.0460
StepF14 - StepF18 0.139521 0.032 Inf 4.359 0.0018
StepF15 - StepF16 0.033536 0.032 Inf 1.048 0.9999
StepF15 - StepF17 0.139236 0.032 Inf 4.350 0.0019
StepF15 - StepF18 0.166254 0.032 Inf 5.194 <.0001
StepF16 - StepF17 0.105699 0.032 Inf 3.302 0.0889
StepF16 - StepF18 0.132718 0.032 Inf 4.146 0.0044
StepF17 - StepF18 0.027019 0.032 Inf 0.844 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.115213 0.032 Inf -3.599 0.0347
StepF1 - StepF3 -0.084028 0.032 Inf -2.625 0.4346
StepF1 - StepF4 -0.057319 0.032 Inf -1.791 0.9469
StepF1 - StepF5 -0.000365 0.032 Inf -0.011 1.0000
StepF1 - StepF6 -0.139372 0.032 Inf -4.354 0.0018
StepF1 - StepF7 -0.010956 0.032 Inf -0.342 1.0000
StepF1 - StepF8 -0.001450 0.032 Inf -0.045 1.0000
StepF1 - StepF9 -0.046816 0.032 Inf -1.463 0.9930
StepF1 - StepF10 0.039705 0.032 Inf 1.240 0.9990
StepF1 - StepF11 0.014342 0.032 Inf 0.448 1.0000
StepF1 - StepF12 0.094244 0.032 Inf 2.944 0.2281
StepF1 - StepF13 0.044322 0.032 Inf 1.385 0.9963
StepF1 - StepF14 0.038434 0.032 Inf 1.201 0.9994
StepF1 - StepF15 0.011701 0.032 Inf 0.366 1.0000
StepF1 - StepF16 0.045237 0.032 Inf 1.413 0.9953
StepF1 - StepF17 0.150937 0.032 Inf 4.715 0.0003
StepF1 - StepF18 0.177955 0.032 Inf 5.559 <.0001
StepF2 - StepF3 0.031185 0.032 Inf 0.974 1.0000
StepF2 - StepF4 0.057894 0.032 Inf 1.809 0.9420
StepF2 - StepF5 0.114848 0.032 Inf 3.588 0.0360
StepF2 - StepF6 -0.024159 0.032 Inf -0.755 1.0000
StepF2 - StepF7 0.104257 0.032 Inf 3.257 0.1013
StepF2 - StepF8 0.113763 0.032 Inf 3.554 0.0404
StepF2 - StepF9 0.068397 0.032 Inf 2.137 0.7947
StepF2 - StepF10 0.154918 0.032 Inf 4.840 0.0002
StepF2 - StepF11 0.129555 0.032 Inf 4.047 0.0066
StepF2 - StepF12 0.209457 0.032 Inf 6.544 <.0001
StepF2 - StepF13 0.159534 0.032 Inf 4.984 0.0001
StepF2 - StepF14 0.153647 0.032 Inf 4.800 0.0002
StepF2 - StepF15 0.126914 0.032 Inf 3.965 0.0091
StepF2 - StepF16 0.160450 0.032 Inf 5.013 0.0001
StepF2 - StepF17 0.266149 0.032 Inf 8.315 <.0001
StepF2 - StepF18 0.293168 0.032 Inf 9.159 <.0001
StepF3 - StepF4 0.026710 0.032 Inf 0.834 1.0000
StepF3 - StepF5 0.083663 0.032 Inf 2.614 0.4431
StepF3 - StepF6 -0.055344 0.032 Inf -1.729 0.9613
StepF3 - StepF7 0.073072 0.032 Inf 2.283 0.6961
StepF3 - StepF8 0.082578 0.032 Inf 2.580 0.4687
StepF3 - StepF9 0.037212 0.032 Inf 1.163 0.9996
StepF3 - StepF10 0.123734 0.032 Inf 3.866 0.0134
StepF3 - StepF11 0.098371 0.032 Inf 3.073 0.1666
StepF3 - StepF12 0.178272 0.032 Inf 5.569 <.0001
StepF3 - StepF13 0.128350 0.032 Inf 4.010 0.0077
StepF3 - StepF14 0.122463 0.032 Inf 3.826 0.0155
StepF3 - StepF15 0.095729 0.032 Inf 2.991 0.2044
StepF3 - StepF16 0.129266 0.032 Inf 4.038 0.0068
StepF3 - StepF17 0.234965 0.032 Inf 7.340 <.0001
StepF3 - StepF18 0.261984 0.032 Inf 8.185 <.0001
StepF4 - StepF5 0.056953 0.032 Inf 1.779 0.9498
StepF4 - StepF6 -0.082054 0.032 Inf -2.563 0.4812
StepF4 - StepF7 0.046363 0.032 Inf 1.448 0.9937
StepF4 - StepF8 0.055868 0.032 Inf 1.745 0.9578
StepF4 - StepF9 0.010502 0.032 Inf 0.328 1.0000
StepF4 - StepF10 0.097024 0.032 Inf 3.031 0.1852
StepF4 - StepF11 0.071661 0.032 Inf 2.239 0.7275
StepF4 - StepF12 0.151562 0.032 Inf 4.735 0.0003
StepF4 - StepF13 0.101640 0.032 Inf 3.175 0.1273
StepF4 - StepF14 0.095753 0.032 Inf 2.991 0.2040
StepF4 - StepF15 0.069020 0.032 Inf 2.156 0.7826
StepF4 - StepF16 0.102556 0.032 Inf 3.204 0.1176
StepF4 - StepF17 0.208255 0.032 Inf 6.506 <.0001
StepF4 - StepF18 0.235274 0.032 Inf 7.350 <.0001
StepF5 - StepF6 -0.139007 0.032 Inf -4.343 0.0019
StepF5 - StepF7 -0.010591 0.032 Inf -0.331 1.0000
StepF5 - StepF8 -0.001085 0.032 Inf -0.034 1.0000
StepF5 - StepF9 -0.046451 0.032 Inf -1.451 0.9936
StepF5 - StepF10 0.040071 0.032 Inf 1.252 0.9989
StepF5 - StepF11 0.014708 0.032 Inf 0.459 1.0000
StepF5 - StepF12 0.094609 0.032 Inf 2.956 0.2221
StepF5 - StepF13 0.044687 0.032 Inf 1.396 0.9959
StepF5 - StepF14 0.038800 0.032 Inf 1.212 0.9993
StepF5 - StepF15 0.012066 0.032 Inf 0.377 1.0000
StepF5 - StepF16 0.045602 0.032 Inf 1.425 0.9948
StepF5 - StepF17 0.151302 0.032 Inf 4.727 0.0003
StepF5 - StepF18 0.178321 0.032 Inf 5.571 <.0001
StepF6 - StepF7 0.128416 0.032 Inf 4.012 0.0076
StepF6 - StepF8 0.137922 0.032 Inf 4.309 0.0022
StepF6 - StepF9 0.092556 0.032 Inf 2.892 0.2571
StepF6 - StepF10 0.179077 0.032 Inf 5.595 <.0001
StepF6 - StepF11 0.153715 0.032 Inf 4.802 0.0002
StepF6 - StepF12 0.233616 0.032 Inf 7.298 <.0001
StepF6 - StepF13 0.183694 0.032 Inf 5.739 <.0001
StepF6 - StepF14 0.177807 0.032 Inf 5.555 <.0001
StepF6 - StepF15 0.151073 0.032 Inf 4.720 0.0003
StepF6 - StepF16 0.184609 0.032 Inf 5.767 <.0001
StepF6 - StepF17 0.290309 0.032 Inf 9.069 <.0001
StepF6 - StepF18 0.317328 0.032 Inf 9.914 <.0001
StepF7 - StepF8 0.009506 0.032 Inf 0.297 1.0000
StepF7 - StepF9 -0.035860 0.032 Inf -1.120 0.9997
StepF7 - StepF10 0.050661 0.032 Inf 1.583 0.9837
StepF7 - StepF11 0.025298 0.032 Inf 0.790 1.0000
StepF7 - StepF12 0.105200 0.032 Inf 3.287 0.0930
StepF7 - StepF13 0.055278 0.032 Inf 1.727 0.9617
StepF7 - StepF14 0.049390 0.032 Inf 1.543 0.9875
StepF7 - StepF15 0.022657 0.032 Inf 0.708 1.0000
StepF7 - StepF16 0.056193 0.032 Inf 1.756 0.9555
StepF7 - StepF17 0.161893 0.032 Inf 5.058 0.0001
StepF7 - StepF18 0.188912 0.032 Inf 5.902 <.0001
StepF8 - StepF9 -0.045366 0.032 Inf -1.417 0.9951
StepF8 - StepF10 0.041155 0.032 Inf 1.286 0.9985
StepF8 - StepF11 0.015793 0.032 Inf 0.493 1.0000
StepF8 - StepF12 0.095694 0.032 Inf 2.990 0.2049
StepF8 - StepF13 0.045772 0.032 Inf 1.430 0.9946
StepF8 - StepF14 0.039885 0.032 Inf 1.246 0.9990
StepF8 - StepF15 0.013151 0.032 Inf 0.411 1.0000
StepF8 - StepF16 0.046687 0.032 Inf 1.459 0.9932
StepF8 - StepF17 0.152387 0.032 Inf 4.761 0.0003
StepF8 - StepF18 0.179406 0.032 Inf 5.605 <.0001
StepF9 - StepF10 0.086521 0.032 Inf 2.703 0.3781
StepF9 - StepF11 0.061158 0.032 Inf 1.911 0.9083
StepF9 - StepF12 0.141060 0.032 Inf 4.407 0.0014
StepF9 - StepF13 0.091138 0.032 Inf 2.847 0.2832
StepF9 - StepF14 0.085250 0.032 Inf 2.663 0.4065
StepF9 - StepF15 0.058517 0.032 Inf 1.828 0.9364
StepF9 - StepF16 0.092053 0.032 Inf 2.876 0.2662
StepF9 - StepF17 0.197753 0.032 Inf 6.178 <.0001
StepF9 - StepF18 0.224772 0.032 Inf 7.022 <.0001
StepF10 - StepF11 -0.025363 0.032 Inf -0.792 1.0000
StepF10 - StepF12 0.054538 0.032 Inf 1.704 0.9663
StepF10 - StepF13 0.004616 0.032 Inf 0.144 1.0000
StepF10 - StepF14 -0.001271 0.032 Inf -0.040 1.0000
StepF10 - StepF15 -0.028004 0.032 Inf -0.875 1.0000
StepF10 - StepF16 0.005532 0.032 Inf 0.173 1.0000
StepF10 - StepF17 0.111231 0.032 Inf 3.475 0.0523
StepF10 - StepF18 0.138250 0.032 Inf 4.319 0.0021
StepF11 - StepF12 0.079901 0.032 Inf 2.496 0.5332
StepF11 - StepF13 0.029979 0.032 Inf 0.937 1.0000
StepF11 - StepF14 0.024092 0.032 Inf 0.753 1.0000
StepF11 - StepF15 -0.002641 0.032 Inf -0.083 1.0000
StepF11 - StepF16 0.030895 0.032 Inf 0.965 1.0000
StepF11 - StepF17 0.136594 0.032 Inf 4.267 0.0026
StepF11 - StepF18 0.163613 0.032 Inf 5.111 <.0001
StepF12 - StepF13 -0.049922 0.032 Inf -1.560 0.9860
StepF12 - StepF14 -0.055809 0.032 Inf -1.744 0.9582
StepF12 - StepF15 -0.082543 0.032 Inf -2.579 0.4696
StepF12 - StepF16 -0.049006 0.032 Inf -1.531 0.9885
StepF12 - StepF17 0.056693 0.032 Inf 1.771 0.9518
StepF12 - StepF18 0.083712 0.032 Inf 2.615 0.4420
StepF13 - StepF14 -0.005887 0.032 Inf -0.184 1.0000
StepF13 - StepF15 -0.032620 0.032 Inf -1.019 0.9999
StepF13 - StepF16 0.000916 0.032 Inf 0.029 1.0000
StepF13 - StepF17 0.106615 0.032 Inf 3.331 0.0817
StepF13 - StepF18 0.133634 0.032 Inf 4.175 0.0039
StepF14 - StepF15 -0.026733 0.032 Inf -0.835 1.0000
StepF14 - StepF16 0.006803 0.032 Inf 0.213 1.0000
StepF14 - StepF17 0.112502 0.032 Inf 3.515 0.0460
StepF14 - StepF18 0.139521 0.032 Inf 4.359 0.0018
StepF15 - StepF16 0.033536 0.032 Inf 1.048 0.9999
StepF15 - StepF17 0.139236 0.032 Inf 4.350 0.0019
StepF15 - StepF18 0.166254 0.032 Inf 5.194 <.0001
StepF16 - StepF17 0.105699 0.032 Inf 3.302 0.0889
StepF16 - StepF18 0.132718 0.032 Inf 4.146 0.0044
StepF17 - StepF18 0.027019 0.032 Inf 0.844 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.11521 0.032 Inf 3.599 0.0048
StepF3 - StepF2 -0.03118 0.032 Inf -0.974 1.0000
StepF4 - StepF3 -0.02671 0.032 Inf -0.834 1.0000
StepF5 - StepF4 -0.05695 0.032 Inf -1.779 0.8272
StepF6 - StepF5 0.13901 0.032 Inf 4.343 0.0002
StepF7 - StepF6 -0.12842 0.032 Inf -4.012 0.0010
StepF8 - StepF7 -0.00951 0.032 Inf -0.297 1.0000
StepF9 - StepF8 0.04537 0.032 Inf 1.417 1.0000
StepF10 - StepF9 -0.08652 0.032 Inf -2.703 0.0893
StepF11 - StepF10 0.02536 0.032 Inf 0.792 1.0000
StepF12 - StepF11 -0.07990 0.032 Inf -2.496 0.1507
StepF13 - StepF12 0.04992 0.032 Inf 1.560 1.0000
StepF14 - StepF13 0.00589 0.032 Inf 0.184 1.0000
StepF15 - StepF14 0.02673 0.032 Inf 0.835 1.0000
StepF16 - StepF15 -0.03354 0.032 Inf -1.048 1.0000
StepF17 - StepF16 -0.10570 0.032 Inf -3.302 0.0134
StepF18 - StepF17 -0.02702 0.032 Inf -0.844 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.11521 0.032 Inf 3.599 0.0048
StepF3 - StepF2 -0.03118 0.032 Inf -0.974 1.0000
StepF4 - StepF3 -0.02671 0.032 Inf -0.834 1.0000
StepF5 - StepF4 -0.05695 0.032 Inf -1.779 0.8272
StepF6 - StepF5 0.13901 0.032 Inf 4.343 0.0002
StepF7 - StepF6 -0.12842 0.032 Inf -4.012 0.0010
StepF8 - StepF7 -0.00951 0.032 Inf -0.297 1.0000
StepF9 - StepF8 0.04537 0.032 Inf 1.417 1.0000
StepF10 - StepF9 -0.08652 0.032 Inf -2.703 0.0893
StepF11 - StepF10 0.02536 0.032 Inf 0.792 1.0000
StepF12 - StepF11 -0.07990 0.032 Inf -2.496 0.1507
StepF13 - StepF12 0.04992 0.032 Inf 1.560 1.0000
StepF14 - StepF13 0.00589 0.032 Inf 0.184 1.0000
StepF15 - StepF14 0.02673 0.032 Inf 0.835 1.0000
StepF16 - StepF15 -0.03354 0.032 Inf -1.048 1.0000
StepF17 - StepF16 -0.10570 0.032 Inf -3.302 0.0134
StepF18 - StepF17 -0.02702 0.032 Inf -0.844 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests
==============================
TEST | Block 4 | 18 steps | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 279.5721 17 <2e-16 ***
Accuracy 0.0015 1 0.9693
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.787 0.0843 Inf 0.622 0.953
2 0.946 0.0843 Inf 0.781 1.112
3 0.903 0.0843 Inf 0.738 1.068
4 0.767 0.0843 Inf 0.602 0.933
5 0.780 0.0843 Inf 0.615 0.946
6 0.907 0.0843 Inf 0.742 1.072
7 0.792 0.0843 Inf 0.627 0.957
8 0.715 0.0843 Inf 0.550 0.880
9 0.758 0.0843 Inf 0.593 0.923
10 0.794 0.0843 Inf 0.629 0.959
11 0.720 0.0843 Inf 0.555 0.885
12 0.643 0.0843 Inf 0.478 0.808
13 0.697 0.0843 Inf 0.532 0.862
14 0.669 0.0843 Inf 0.504 0.834
15 0.712 0.0843 Inf 0.547 0.877
16 0.686 0.0843 Inf 0.520 0.851
17 0.641 0.0843 Inf 0.476 0.806
18 0.583 0.0843 Inf 0.418 0.748
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.787 0.0837 Inf 0.623 0.951
2 0.946 0.0837 Inf 0.782 1.110
3 0.902 0.0837 Inf 0.738 1.066
4 0.767 0.0837 Inf 0.603 0.931
5 0.780 0.0837 Inf 0.616 0.944
6 0.907 0.0837 Inf 0.743 1.071
7 0.792 0.0837 Inf 0.628 0.956
8 0.714 0.0837 Inf 0.550 0.878
9 0.757 0.0837 Inf 0.593 0.921
10 0.794 0.0837 Inf 0.630 0.958
11 0.719 0.0837 Inf 0.555 0.883
12 0.642 0.0837 Inf 0.478 0.806
13 0.696 0.0837 Inf 0.532 0.860
14 0.669 0.0837 Inf 0.505 0.833
15 0.712 0.0837 Inf 0.548 0.876
16 0.685 0.0837 Inf 0.521 0.849
17 0.641 0.0837 Inf 0.477 0.805
18 0.582 0.0837 Inf 0.418 0.746
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.15901 0.034 Inf -4.680 0.0004
StepF1 - StepF3 -0.11530 0.034 Inf -3.394 0.0675
StepF1 - StepF4 0.02004 0.034 Inf 0.590 1.0000
StepF1 - StepF5 0.00692 0.034 Inf 0.204 1.0000
StepF1 - StepF6 -0.11991 0.034 Inf -3.529 0.0438
StepF1 - StepF7 -0.00491 0.034 Inf -0.145 1.0000
StepF1 - StepF8 0.07264 0.034 Inf 2.138 0.7940
StepF1 - StepF9 0.02965 0.034 Inf 0.873 1.0000
StepF1 - StepF10 -0.00688 0.034 Inf -0.202 1.0000
StepF1 - StepF11 0.06732 0.034 Inf 1.981 0.8785
StepF1 - StepF12 0.14453 0.034 Inf 4.254 0.0028
StepF1 - StepF13 0.09039 0.034 Inf 2.660 0.4086
StepF1 - StepF14 0.11811 0.034 Inf 3.476 0.0521
StepF1 - StepF15 0.07517 0.034 Inf 2.212 0.7457
StepF1 - StepF16 0.10186 0.034 Inf 2.998 0.2008
StepF1 - StepF17 0.14624 0.034 Inf 4.304 0.0023
StepF1 - StepF18 0.20450 0.034 Inf 6.019 <.0001
StepF2 - StepF3 0.04371 0.034 Inf 1.287 0.9985
StepF2 - StepF4 0.17905 0.034 Inf 5.270 <.0001
StepF2 - StepF5 0.16593 0.034 Inf 4.884 0.0002
StepF2 - StepF6 0.03910 0.034 Inf 1.151 0.9996
StepF2 - StepF7 0.15410 0.034 Inf 4.535 0.0008
StepF2 - StepF8 0.23165 0.034 Inf 6.818 <.0001
StepF2 - StepF9 0.18866 0.034 Inf 5.553 <.0001
StepF2 - StepF10 0.15213 0.034 Inf 4.478 0.0010
StepF2 - StepF11 0.22633 0.034 Inf 6.661 <.0001
StepF2 - StepF12 0.30354 0.034 Inf 8.934 <.0001
StepF2 - StepF13 0.24940 0.034 Inf 7.340 <.0001
StepF2 - StepF14 0.27712 0.034 Inf 8.156 <.0001
StepF2 - StepF15 0.23418 0.034 Inf 6.892 <.0001
StepF2 - StepF16 0.26087 0.034 Inf 7.678 <.0001
StepF2 - StepF17 0.30525 0.034 Inf 8.984 <.0001
StepF2 - StepF18 0.36351 0.034 Inf 10.699 <.0001
StepF3 - StepF4 0.13534 0.034 Inf 3.983 0.0085
StepF3 - StepF5 0.12222 0.034 Inf 3.597 0.0349
StepF3 - StepF6 -0.00461 0.034 Inf -0.136 1.0000
StepF3 - StepF7 0.11038 0.034 Inf 3.249 0.1037
StepF3 - StepF8 0.18794 0.034 Inf 5.531 <.0001
StepF3 - StepF9 0.14495 0.034 Inf 4.266 0.0027
StepF3 - StepF10 0.10842 0.034 Inf 3.191 0.1219
StepF3 - StepF11 0.18262 0.034 Inf 5.375 <.0001
StepF3 - StepF12 0.25983 0.034 Inf 7.648 <.0001
StepF3 - StepF13 0.20569 0.034 Inf 6.054 <.0001
StepF3 - StepF14 0.23340 0.034 Inf 6.870 <.0001
StepF3 - StepF15 0.19047 0.034 Inf 5.606 <.0001
StepF3 - StepF16 0.21716 0.034 Inf 6.391 <.0001
StepF3 - StepF17 0.26154 0.034 Inf 7.698 <.0001
StepF3 - StepF18 0.31980 0.034 Inf 9.412 <.0001
StepF4 - StepF5 -0.01312 0.034 Inf -0.386 1.0000
StepF4 - StepF6 -0.13995 0.034 Inf -4.119 0.0049
StepF4 - StepF7 -0.02495 0.034 Inf -0.734 1.0000
StepF4 - StepF8 0.05260 0.034 Inf 1.548 0.9871
StepF4 - StepF9 0.00961 0.034 Inf 0.283 1.0000
StepF4 - StepF10 -0.02692 0.034 Inf -0.792 1.0000
StepF4 - StepF11 0.04728 0.034 Inf 1.392 0.9960
StepF4 - StepF12 0.12449 0.034 Inf 3.664 0.0277
StepF4 - StepF13 0.07035 0.034 Inf 2.071 0.8335
StepF4 - StepF14 0.09807 0.034 Inf 2.886 0.2601
StepF4 - StepF15 0.05513 0.034 Inf 1.623 0.9791
StepF4 - StepF16 0.08182 0.034 Inf 2.408 0.6017
StepF4 - StepF17 0.12620 0.034 Inf 3.714 0.0232
StepF4 - StepF18 0.18446 0.034 Inf 5.429 <.0001
StepF5 - StepF6 -0.12683 0.034 Inf -3.733 0.0218
StepF5 - StepF7 -0.01184 0.034 Inf -0.348 1.0000
StepF5 - StepF8 0.06572 0.034 Inf 1.934 0.8990
StepF5 - StepF9 0.02273 0.034 Inf 0.669 1.0000
StepF5 - StepF10 -0.01380 0.034 Inf -0.406 1.0000
StepF5 - StepF11 0.06040 0.034 Inf 1.778 0.9502
StepF5 - StepF12 0.13761 0.034 Inf 4.050 0.0065
StepF5 - StepF13 0.08347 0.034 Inf 2.457 0.5640
StepF5 - StepF14 0.11118 0.034 Inf 3.272 0.0969
StepF5 - StepF15 0.06825 0.034 Inf 2.009 0.8657
StepF5 - StepF16 0.09494 0.034 Inf 2.794 0.3164
StepF5 - StepF17 0.13931 0.034 Inf 4.100 0.0053
StepF5 - StepF18 0.19758 0.034 Inf 5.815 <.0001
StepF6 - StepF7 0.11499 0.034 Inf 3.385 0.0694
StepF6 - StepF8 0.19254 0.034 Inf 5.667 <.0001
StepF6 - StepF9 0.14956 0.034 Inf 4.402 0.0015
StepF6 - StepF10 0.11303 0.034 Inf 3.327 0.0826
StepF6 - StepF11 0.18723 0.034 Inf 5.511 <.0001
StepF6 - StepF12 0.26444 0.034 Inf 7.783 <.0001
StepF6 - StepF13 0.21029 0.034 Inf 6.190 <.0001
StepF6 - StepF14 0.23801 0.034 Inf 7.005 <.0001
StepF6 - StepF15 0.19507 0.034 Inf 5.742 <.0001
StepF6 - StepF16 0.22177 0.034 Inf 6.527 <.0001
StepF6 - StepF17 0.26614 0.034 Inf 7.833 <.0001
StepF6 - StepF18 0.32441 0.034 Inf 9.548 <.0001
StepF7 - StepF8 0.07755 0.034 Inf 2.283 0.6963
StepF7 - StepF9 0.03456 0.034 Inf 1.017 0.9999
StepF7 - StepF10 -0.00197 0.034 Inf -0.058 1.0000
StepF7 - StepF11 0.07223 0.034 Inf 2.126 0.8013
StepF7 - StepF12 0.14945 0.034 Inf 4.399 0.0015
StepF7 - StepF13 0.09530 0.034 Inf 2.805 0.3095
StepF7 - StepF14 0.12302 0.034 Inf 3.621 0.0322
StepF7 - StepF15 0.08008 0.034 Inf 2.357 0.6409
StepF7 - StepF16 0.10677 0.034 Inf 3.143 0.1390
StepF7 - StepF17 0.15115 0.034 Inf 4.449 0.0012
StepF7 - StepF18 0.20941 0.034 Inf 6.164 <.0001
StepF8 - StepF9 -0.04299 0.034 Inf -1.265 0.9987
StepF8 - StepF10 -0.07952 0.034 Inf -2.340 0.6534
StepF8 - StepF11 -0.00532 0.034 Inf -0.157 1.0000
StepF8 - StepF12 0.07189 0.034 Inf 2.116 0.8073
StepF8 - StepF13 0.01775 0.034 Inf 0.522 1.0000
StepF8 - StepF14 0.04547 0.034 Inf 1.338 0.9975
StepF8 - StepF15 0.00253 0.034 Inf 0.074 1.0000
StepF8 - StepF16 0.02922 0.034 Inf 0.860 1.0000
StepF8 - StepF17 0.07360 0.034 Inf 2.166 0.7762
StepF8 - StepF18 0.13186 0.034 Inf 3.881 0.0126
StepF9 - StepF10 -0.03653 0.034 Inf -1.075 0.9999
StepF9 - StepF11 0.03767 0.034 Inf 1.109 0.9998
StepF9 - StepF12 0.11488 0.034 Inf 3.381 0.0701
StepF9 - StepF13 0.06074 0.034 Inf 1.788 0.9477
StepF9 - StepF14 0.08846 0.034 Inf 2.603 0.4508
StepF9 - StepF15 0.04552 0.034 Inf 1.340 0.9975
StepF9 - StepF16 0.07221 0.034 Inf 2.125 0.8018
StepF9 - StepF17 0.11659 0.034 Inf 3.431 0.0600
StepF9 - StepF18 0.17485 0.034 Inf 5.146 <.0001
StepF10 - StepF11 0.07420 0.034 Inf 2.184 0.7647
StepF10 - StepF12 0.15141 0.034 Inf 4.456 0.0012
StepF10 - StepF13 0.09727 0.034 Inf 2.863 0.2738
StepF10 - StepF14 0.12499 0.034 Inf 3.679 0.0264
StepF10 - StepF15 0.08205 0.034 Inf 2.415 0.5964
StepF10 - StepF16 0.10874 0.034 Inf 3.200 0.1188
StepF10 - StepF17 0.15312 0.034 Inf 4.507 0.0009
StepF10 - StepF18 0.21138 0.034 Inf 6.221 <.0001
StepF11 - StepF12 0.07721 0.034 Inf 2.273 0.7035
StepF11 - StepF13 0.02307 0.034 Inf 0.679 1.0000
StepF11 - StepF14 0.05079 0.034 Inf 1.495 0.9911
StepF11 - StepF15 0.00785 0.034 Inf 0.231 1.0000
StepF11 - StepF16 0.03454 0.034 Inf 1.017 0.9999
StepF11 - StepF17 0.07892 0.034 Inf 2.323 0.6667
StepF11 - StepF18 0.13718 0.034 Inf 4.038 0.0069
StepF12 - StepF13 -0.05415 0.034 Inf -1.594 0.9825
StepF12 - StepF14 -0.02643 0.034 Inf -0.778 1.0000
StepF12 - StepF15 -0.06936 0.034 Inf -2.042 0.8490
StepF12 - StepF16 -0.04267 0.034 Inf -1.256 0.9989
StepF12 - StepF17 0.00170 0.034 Inf 0.050 1.0000
StepF12 - StepF18 0.05997 0.034 Inf 1.765 0.9533
StepF13 - StepF14 0.02772 0.034 Inf 0.816 1.0000
StepF13 - StepF15 -0.01522 0.034 Inf -0.448 1.0000
StepF13 - StepF16 0.01147 0.034 Inf 0.338 1.0000
StepF13 - StepF17 0.05585 0.034 Inf 1.644 0.9762
StepF13 - StepF18 0.11411 0.034 Inf 3.359 0.0751
StepF14 - StepF15 -0.04294 0.034 Inf -1.264 0.9988
StepF14 - StepF16 -0.01625 0.034 Inf -0.478 1.0000
StepF14 - StepF17 0.02813 0.034 Inf 0.828 1.0000
StepF14 - StepF18 0.08639 0.034 Inf 2.543 0.4971
StepF15 - StepF16 0.02669 0.034 Inf 0.786 1.0000
StepF15 - StepF17 0.07107 0.034 Inf 2.092 0.8215
StepF15 - StepF18 0.12933 0.034 Inf 3.807 0.0166
StepF16 - StepF17 0.04438 0.034 Inf 1.306 0.9981
StepF16 - StepF18 0.10264 0.034 Inf 3.021 0.1899
StepF17 - StepF18 0.05826 0.034 Inf 1.715 0.9642
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.15901 0.034 Inf -4.680 0.0004
StepF1 - StepF3 -0.11530 0.034 Inf -3.394 0.0675
StepF1 - StepF4 0.02004 0.034 Inf 0.590 1.0000
StepF1 - StepF5 0.00692 0.034 Inf 0.204 1.0000
StepF1 - StepF6 -0.11991 0.034 Inf -3.529 0.0438
StepF1 - StepF7 -0.00491 0.034 Inf -0.145 1.0000
StepF1 - StepF8 0.07264 0.034 Inf 2.138 0.7940
StepF1 - StepF9 0.02965 0.034 Inf 0.873 1.0000
StepF1 - StepF10 -0.00688 0.034 Inf -0.202 1.0000
StepF1 - StepF11 0.06732 0.034 Inf 1.981 0.8785
StepF1 - StepF12 0.14453 0.034 Inf 4.254 0.0028
StepF1 - StepF13 0.09039 0.034 Inf 2.660 0.4086
StepF1 - StepF14 0.11811 0.034 Inf 3.476 0.0521
StepF1 - StepF15 0.07517 0.034 Inf 2.212 0.7457
StepF1 - StepF16 0.10186 0.034 Inf 2.998 0.2008
StepF1 - StepF17 0.14624 0.034 Inf 4.304 0.0023
StepF1 - StepF18 0.20450 0.034 Inf 6.019 <.0001
StepF2 - StepF3 0.04371 0.034 Inf 1.287 0.9985
StepF2 - StepF4 0.17905 0.034 Inf 5.270 <.0001
StepF2 - StepF5 0.16593 0.034 Inf 4.884 0.0002
StepF2 - StepF6 0.03910 0.034 Inf 1.151 0.9996
StepF2 - StepF7 0.15410 0.034 Inf 4.535 0.0008
StepF2 - StepF8 0.23165 0.034 Inf 6.818 <.0001
StepF2 - StepF9 0.18866 0.034 Inf 5.553 <.0001
StepF2 - StepF10 0.15213 0.034 Inf 4.478 0.0010
StepF2 - StepF11 0.22633 0.034 Inf 6.661 <.0001
StepF2 - StepF12 0.30354 0.034 Inf 8.934 <.0001
StepF2 - StepF13 0.24940 0.034 Inf 7.340 <.0001
StepF2 - StepF14 0.27712 0.034 Inf 8.156 <.0001
StepF2 - StepF15 0.23418 0.034 Inf 6.892 <.0001
StepF2 - StepF16 0.26087 0.034 Inf 7.678 <.0001
StepF2 - StepF17 0.30525 0.034 Inf 8.984 <.0001
StepF2 - StepF18 0.36351 0.034 Inf 10.699 <.0001
StepF3 - StepF4 0.13534 0.034 Inf 3.983 0.0085
StepF3 - StepF5 0.12222 0.034 Inf 3.597 0.0349
StepF3 - StepF6 -0.00461 0.034 Inf -0.136 1.0000
StepF3 - StepF7 0.11038 0.034 Inf 3.249 0.1037
StepF3 - StepF8 0.18794 0.034 Inf 5.531 <.0001
StepF3 - StepF9 0.14495 0.034 Inf 4.266 0.0027
StepF3 - StepF10 0.10842 0.034 Inf 3.191 0.1219
StepF3 - StepF11 0.18262 0.034 Inf 5.375 <.0001
StepF3 - StepF12 0.25983 0.034 Inf 7.648 <.0001
StepF3 - StepF13 0.20569 0.034 Inf 6.054 <.0001
StepF3 - StepF14 0.23340 0.034 Inf 6.870 <.0001
StepF3 - StepF15 0.19047 0.034 Inf 5.606 <.0001
StepF3 - StepF16 0.21716 0.034 Inf 6.391 <.0001
StepF3 - StepF17 0.26154 0.034 Inf 7.698 <.0001
StepF3 - StepF18 0.31980 0.034 Inf 9.412 <.0001
StepF4 - StepF5 -0.01312 0.034 Inf -0.386 1.0000
StepF4 - StepF6 -0.13995 0.034 Inf -4.119 0.0049
StepF4 - StepF7 -0.02495 0.034 Inf -0.734 1.0000
StepF4 - StepF8 0.05260 0.034 Inf 1.548 0.9871
StepF4 - StepF9 0.00961 0.034 Inf 0.283 1.0000
StepF4 - StepF10 -0.02692 0.034 Inf -0.792 1.0000
StepF4 - StepF11 0.04728 0.034 Inf 1.392 0.9960
StepF4 - StepF12 0.12449 0.034 Inf 3.664 0.0277
StepF4 - StepF13 0.07035 0.034 Inf 2.071 0.8335
StepF4 - StepF14 0.09807 0.034 Inf 2.886 0.2601
StepF4 - StepF15 0.05513 0.034 Inf 1.623 0.9791
StepF4 - StepF16 0.08182 0.034 Inf 2.408 0.6017
StepF4 - StepF17 0.12620 0.034 Inf 3.714 0.0232
StepF4 - StepF18 0.18446 0.034 Inf 5.429 <.0001
StepF5 - StepF6 -0.12683 0.034 Inf -3.733 0.0218
StepF5 - StepF7 -0.01184 0.034 Inf -0.348 1.0000
StepF5 - StepF8 0.06572 0.034 Inf 1.934 0.8990
StepF5 - StepF9 0.02273 0.034 Inf 0.669 1.0000
StepF5 - StepF10 -0.01380 0.034 Inf -0.406 1.0000
StepF5 - StepF11 0.06040 0.034 Inf 1.778 0.9502
StepF5 - StepF12 0.13761 0.034 Inf 4.050 0.0065
StepF5 - StepF13 0.08347 0.034 Inf 2.457 0.5640
StepF5 - StepF14 0.11118 0.034 Inf 3.272 0.0969
StepF5 - StepF15 0.06825 0.034 Inf 2.009 0.8657
StepF5 - StepF16 0.09494 0.034 Inf 2.794 0.3164
StepF5 - StepF17 0.13931 0.034 Inf 4.100 0.0053
StepF5 - StepF18 0.19758 0.034 Inf 5.815 <.0001
StepF6 - StepF7 0.11499 0.034 Inf 3.385 0.0694
StepF6 - StepF8 0.19254 0.034 Inf 5.667 <.0001
StepF6 - StepF9 0.14956 0.034 Inf 4.402 0.0015
StepF6 - StepF10 0.11303 0.034 Inf 3.327 0.0826
StepF6 - StepF11 0.18723 0.034 Inf 5.511 <.0001
StepF6 - StepF12 0.26444 0.034 Inf 7.783 <.0001
StepF6 - StepF13 0.21029 0.034 Inf 6.190 <.0001
StepF6 - StepF14 0.23801 0.034 Inf 7.005 <.0001
StepF6 - StepF15 0.19507 0.034 Inf 5.742 <.0001
StepF6 - StepF16 0.22177 0.034 Inf 6.527 <.0001
StepF6 - StepF17 0.26614 0.034 Inf 7.833 <.0001
StepF6 - StepF18 0.32441 0.034 Inf 9.548 <.0001
StepF7 - StepF8 0.07755 0.034 Inf 2.283 0.6963
StepF7 - StepF9 0.03456 0.034 Inf 1.017 0.9999
StepF7 - StepF10 -0.00197 0.034 Inf -0.058 1.0000
StepF7 - StepF11 0.07223 0.034 Inf 2.126 0.8013
StepF7 - StepF12 0.14945 0.034 Inf 4.399 0.0015
StepF7 - StepF13 0.09530 0.034 Inf 2.805 0.3095
StepF7 - StepF14 0.12302 0.034 Inf 3.621 0.0322
StepF7 - StepF15 0.08008 0.034 Inf 2.357 0.6409
StepF7 - StepF16 0.10677 0.034 Inf 3.143 0.1390
StepF7 - StepF17 0.15115 0.034 Inf 4.449 0.0012
StepF7 - StepF18 0.20941 0.034 Inf 6.164 <.0001
StepF8 - StepF9 -0.04299 0.034 Inf -1.265 0.9987
StepF8 - StepF10 -0.07952 0.034 Inf -2.340 0.6534
StepF8 - StepF11 -0.00532 0.034 Inf -0.157 1.0000
StepF8 - StepF12 0.07189 0.034 Inf 2.116 0.8073
StepF8 - StepF13 0.01775 0.034 Inf 0.522 1.0000
StepF8 - StepF14 0.04547 0.034 Inf 1.338 0.9975
StepF8 - StepF15 0.00253 0.034 Inf 0.074 1.0000
StepF8 - StepF16 0.02922 0.034 Inf 0.860 1.0000
StepF8 - StepF17 0.07360 0.034 Inf 2.166 0.7762
StepF8 - StepF18 0.13186 0.034 Inf 3.881 0.0126
StepF9 - StepF10 -0.03653 0.034 Inf -1.075 0.9999
StepF9 - StepF11 0.03767 0.034 Inf 1.109 0.9998
StepF9 - StepF12 0.11488 0.034 Inf 3.381 0.0701
StepF9 - StepF13 0.06074 0.034 Inf 1.788 0.9477
StepF9 - StepF14 0.08846 0.034 Inf 2.603 0.4508
StepF9 - StepF15 0.04552 0.034 Inf 1.340 0.9975
StepF9 - StepF16 0.07221 0.034 Inf 2.125 0.8018
StepF9 - StepF17 0.11659 0.034 Inf 3.431 0.0600
StepF9 - StepF18 0.17485 0.034 Inf 5.146 <.0001
StepF10 - StepF11 0.07420 0.034 Inf 2.184 0.7647
StepF10 - StepF12 0.15141 0.034 Inf 4.456 0.0012
StepF10 - StepF13 0.09727 0.034 Inf 2.863 0.2738
StepF10 - StepF14 0.12499 0.034 Inf 3.679 0.0264
StepF10 - StepF15 0.08205 0.034 Inf 2.415 0.5964
StepF10 - StepF16 0.10874 0.034 Inf 3.200 0.1188
StepF10 - StepF17 0.15312 0.034 Inf 4.507 0.0009
StepF10 - StepF18 0.21138 0.034 Inf 6.221 <.0001
StepF11 - StepF12 0.07721 0.034 Inf 2.273 0.7035
StepF11 - StepF13 0.02307 0.034 Inf 0.679 1.0000
StepF11 - StepF14 0.05079 0.034 Inf 1.495 0.9911
StepF11 - StepF15 0.00785 0.034 Inf 0.231 1.0000
StepF11 - StepF16 0.03454 0.034 Inf 1.017 0.9999
StepF11 - StepF17 0.07892 0.034 Inf 2.323 0.6667
StepF11 - StepF18 0.13718 0.034 Inf 4.038 0.0069
StepF12 - StepF13 -0.05415 0.034 Inf -1.594 0.9825
StepF12 - StepF14 -0.02643 0.034 Inf -0.778 1.0000
StepF12 - StepF15 -0.06936 0.034 Inf -2.042 0.8490
StepF12 - StepF16 -0.04267 0.034 Inf -1.256 0.9989
StepF12 - StepF17 0.00170 0.034 Inf 0.050 1.0000
StepF12 - StepF18 0.05997 0.034 Inf 1.765 0.9533
StepF13 - StepF14 0.02772 0.034 Inf 0.816 1.0000
StepF13 - StepF15 -0.01522 0.034 Inf -0.448 1.0000
StepF13 - StepF16 0.01147 0.034 Inf 0.338 1.0000
StepF13 - StepF17 0.05585 0.034 Inf 1.644 0.9762
StepF13 - StepF18 0.11411 0.034 Inf 3.359 0.0751
StepF14 - StepF15 -0.04294 0.034 Inf -1.264 0.9988
StepF14 - StepF16 -0.01625 0.034 Inf -0.478 1.0000
StepF14 - StepF17 0.02813 0.034 Inf 0.828 1.0000
StepF14 - StepF18 0.08639 0.034 Inf 2.543 0.4971
StepF15 - StepF16 0.02669 0.034 Inf 0.786 1.0000
StepF15 - StepF17 0.07107 0.034 Inf 2.092 0.8215
StepF15 - StepF18 0.12933 0.034 Inf 3.807 0.0166
StepF16 - StepF17 0.04438 0.034 Inf 1.306 0.9981
StepF16 - StepF18 0.10264 0.034 Inf 3.021 0.1899
StepF17 - StepF18 0.05826 0.034 Inf 1.715 0.9642
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.1590 0.034 Inf 4.680 <.0001
StepF3 - StepF2 -0.0437 0.034 Inf -1.287 1.0000
StepF4 - StepF3 -0.1353 0.034 Inf -3.983 0.0011
StepF5 - StepF4 0.0131 0.034 Inf 0.386 1.0000
StepF6 - StepF5 0.1268 0.034 Inf 3.733 0.0028
StepF7 - StepF6 -0.1150 0.034 Inf -3.385 0.0100
StepF8 - StepF7 -0.0776 0.034 Inf -2.283 0.2919
StepF9 - StepF8 0.0430 0.034 Inf 1.265 1.0000
StepF10 - StepF9 0.0365 0.034 Inf 1.075 1.0000
StepF11 - StepF10 -0.0742 0.034 Inf -2.184 0.3187
StepF12 - StepF11 -0.0772 0.034 Inf -2.273 0.2919
StepF13 - StepF12 0.0541 0.034 Inf 1.594 0.9991
StepF14 - StepF13 -0.0277 0.034 Inf -0.816 1.0000
StepF15 - StepF14 0.0429 0.034 Inf 1.264 1.0000
StepF16 - StepF15 -0.0267 0.034 Inf -0.786 1.0000
StepF17 - StepF16 -0.0444 0.034 Inf -1.306 1.0000
StepF18 - StepF17 -0.0583 0.034 Inf -1.715 0.8638
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.1590 0.034 Inf 4.680 <.0001
StepF3 - StepF2 -0.0437 0.034 Inf -1.287 1.0000
StepF4 - StepF3 -0.1353 0.034 Inf -3.983 0.0011
StepF5 - StepF4 0.0131 0.034 Inf 0.386 1.0000
StepF6 - StepF5 0.1268 0.034 Inf 3.733 0.0028
StepF7 - StepF6 -0.1150 0.034 Inf -3.385 0.0100
StepF8 - StepF7 -0.0776 0.034 Inf -2.283 0.2919
StepF9 - StepF8 0.0430 0.034 Inf 1.265 1.0000
StepF10 - StepF9 0.0365 0.034 Inf 1.075 1.0000
StepF11 - StepF10 -0.0742 0.034 Inf -2.184 0.3187
StepF12 - StepF11 -0.0772 0.034 Inf -2.273 0.2919
StepF13 - StepF12 0.0541 0.034 Inf 1.594 0.9991
StepF14 - StepF13 -0.0277 0.034 Inf -0.816 1.0000
StepF15 - StepF14 0.0429 0.034 Inf 1.264 1.0000
StepF16 - StepF15 -0.0267 0.034 Inf -0.786 1.0000
StepF17 - StepF16 -0.0444 0.034 Inf -1.306 1.0000
StepF18 - StepF17 -0.0583 0.034 Inf -1.715 0.8638
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests
==============================
TEST | Block 4 | 18 steps | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 304.2874 17 <2e-16 ***
Accuracy 0.0009 1 0.9762
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.593 0.153 Inf 1.293 1.89
2 1.807 0.153 Inf 1.506 2.11
3 1.740 0.153 Inf 1.440 2.04
4 1.618 0.153 Inf 1.318 1.92
5 1.467 0.153 Inf 1.166 1.77
6 1.582 0.153 Inf 1.282 1.88
7 1.521 0.153 Inf 1.221 1.82
8 1.529 0.153 Inf 1.228 1.83
9 1.463 0.153 Inf 1.162 1.76
10 1.496 0.153 Inf 1.196 1.80
11 1.543 0.153 Inf 1.242 1.84
12 1.359 0.153 Inf 1.059 1.66
13 1.382 0.153 Inf 1.082 1.68
14 1.470 0.153 Inf 1.170 1.77
15 1.449 0.153 Inf 1.149 1.75
16 1.267 0.153 Inf 0.966 1.57
17 1.252 0.153 Inf 0.951 1.55
18 0.989 0.153 Inf 0.689 1.29
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.594 0.152 Inf 1.296 1.89
2 1.808 0.152 Inf 1.509 2.11
3 1.741 0.152 Inf 1.443 2.04
4 1.619 0.152 Inf 1.321 1.92
5 1.467 0.152 Inf 1.169 1.77
6 1.583 0.152 Inf 1.285 1.88
7 1.522 0.152 Inf 1.224 1.82
8 1.530 0.152 Inf 1.231 1.83
9 1.463 0.152 Inf 1.165 1.76
10 1.497 0.152 Inf 1.199 1.80
11 1.543 0.152 Inf 1.245 1.84
12 1.360 0.152 Inf 1.062 1.66
13 1.383 0.152 Inf 1.085 1.68
14 1.471 0.152 Inf 1.173 1.77
15 1.450 0.152 Inf 1.152 1.75
16 1.268 0.152 Inf 0.969 1.57
17 1.252 0.152 Inf 0.954 1.55
18 0.990 0.152 Inf 0.692 1.29
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.21381 0.0622 Inf -3.437 0.0590
StepF1 - StepF3 -0.14736 0.0622 Inf -2.369 0.6320
StepF1 - StepF4 -0.02536 0.0622 Inf -0.408 1.0000
StepF1 - StepF5 0.12653 0.0622 Inf 2.034 0.8530
StepF1 - StepF6 0.01057 0.0622 Inf 0.170 1.0000
StepF1 - StepF7 0.07195 0.0622 Inf 1.156 0.9996
StepF1 - StepF8 0.06429 0.0622 Inf 1.033 0.9999
StepF1 - StepF9 0.13047 0.0622 Inf 2.097 0.8184
StepF1 - StepF10 0.09693 0.0622 Inf 1.558 0.9862
StepF1 - StepF11 0.05051 0.0622 Inf 0.812 1.0000
StepF1 - StepF12 0.23394 0.0622 Inf 3.760 0.0197
StepF1 - StepF13 0.21087 0.0622 Inf 3.390 0.0683
StepF1 - StepF14 0.12281 0.0622 Inf 1.974 0.8819
StepF1 - StepF15 0.14375 0.0622 Inf 2.311 0.6757
StepF1 - StepF16 0.32639 0.0622 Inf 5.246 <.0001
StepF1 - StepF17 0.34148 0.0622 Inf 5.489 <.0001
StepF1 - StepF18 0.60380 0.0622 Inf 9.705 <.0001
StepF2 - StepF3 0.06645 0.0622 Inf 1.068 0.9999
StepF2 - StepF4 0.18844 0.0622 Inf 3.029 0.1861
StepF2 - StepF5 0.34033 0.0622 Inf 5.471 <.0001
StepF2 - StepF6 0.22437 0.0622 Inf 3.607 0.0338
StepF2 - StepF7 0.28575 0.0622 Inf 4.593 0.0006
StepF2 - StepF8 0.27809 0.0622 Inf 4.470 0.0011
StepF2 - StepF9 0.34428 0.0622 Inf 5.534 <.0001
StepF2 - StepF10 0.31074 0.0622 Inf 4.995 0.0001
StepF2 - StepF11 0.26432 0.0622 Inf 4.249 0.0029
StepF2 - StepF12 0.44774 0.0622 Inf 7.197 <.0001
StepF2 - StepF13 0.42468 0.0622 Inf 6.826 <.0001
StepF2 - StepF14 0.33662 0.0622 Inf 5.411 <.0001
StepF2 - StepF15 0.35756 0.0622 Inf 5.747 <.0001
StepF2 - StepF16 0.54019 0.0622 Inf 8.683 <.0001
StepF2 - StepF17 0.55529 0.0622 Inf 8.926 <.0001
StepF2 - StepF18 0.81760 0.0622 Inf 13.142 <.0001
StepF3 - StepF4 0.12200 0.0622 Inf 1.961 0.8877
StepF3 - StepF5 0.27389 0.0622 Inf 4.402 0.0015
StepF3 - StepF6 0.15793 0.0622 Inf 2.539 0.5004
StepF3 - StepF7 0.21931 0.0622 Inf 3.525 0.0444
StepF3 - StepF8 0.21165 0.0622 Inf 3.402 0.0658
StepF3 - StepF9 0.27783 0.0622 Inf 4.466 0.0011
StepF3 - StepF10 0.24430 0.0622 Inf 3.927 0.0106
StepF3 - StepF11 0.19787 0.0622 Inf 3.181 0.1254
StepF3 - StepF12 0.38130 0.0622 Inf 6.129 <.0001
StepF3 - StepF13 0.35823 0.0622 Inf 5.758 <.0001
StepF3 - StepF14 0.27018 0.0622 Inf 4.343 0.0019
StepF3 - StepF15 0.29111 0.0622 Inf 4.679 0.0004
StepF3 - StepF16 0.47375 0.0622 Inf 7.615 <.0001
StepF3 - StepF17 0.48885 0.0622 Inf 7.858 <.0001
StepF3 - StepF18 0.75116 0.0622 Inf 12.074 <.0001
StepF4 - StepF5 0.15189 0.0622 Inf 2.441 0.5758
StepF4 - StepF6 0.03593 0.0622 Inf 0.578 1.0000
StepF4 - StepF7 0.09731 0.0622 Inf 1.564 0.9856
StepF4 - StepF8 0.08965 0.0622 Inf 1.441 0.9941
StepF4 - StepF9 0.15583 0.0622 Inf 2.505 0.5264
StepF4 - StepF10 0.12230 0.0622 Inf 1.966 0.8856
StepF4 - StepF11 0.07588 0.0622 Inf 1.220 0.9992
StepF4 - StepF12 0.25930 0.0622 Inf 4.168 0.0040
StepF4 - StepF13 0.23623 0.0622 Inf 3.797 0.0172
StepF4 - StepF14 0.14818 0.0622 Inf 2.382 0.6219
StepF4 - StepF15 0.16911 0.0622 Inf 2.718 0.3673
StepF4 - StepF16 0.35175 0.0622 Inf 5.654 <.0001
StepF4 - StepF17 0.36685 0.0622 Inf 5.897 <.0001
StepF4 - StepF18 0.62916 0.0622 Inf 10.113 <.0001
StepF5 - StepF6 -0.11596 0.0622 Inf -1.864 0.9250
StepF5 - StepF7 -0.05458 0.0622 Inf -0.877 1.0000
StepF5 - StepF8 -0.06224 0.0622 Inf -1.000 0.9999
StepF5 - StepF9 0.00394 0.0622 Inf 0.063 1.0000
StepF5 - StepF10 -0.02959 0.0622 Inf -0.476 1.0000
StepF5 - StepF11 -0.07602 0.0622 Inf -1.222 0.9992
StepF5 - StepF12 0.10741 0.0622 Inf 1.727 0.9618
StepF5 - StepF13 0.08434 0.0622 Inf 1.356 0.9971
StepF5 - StepF14 -0.00371 0.0622 Inf -0.060 1.0000
StepF5 - StepF15 0.01722 0.0622 Inf 0.277 1.0000
StepF5 - StepF16 0.19986 0.0622 Inf 3.213 0.1148
StepF5 - StepF17 0.21496 0.0622 Inf 3.455 0.0557
StepF5 - StepF18 0.47727 0.0622 Inf 7.672 <.0001
StepF6 - StepF7 0.06138 0.0622 Inf 0.987 1.0000
StepF6 - StepF8 0.05372 0.0622 Inf 0.864 1.0000
StepF6 - StepF9 0.11990 0.0622 Inf 1.927 0.9018
StepF6 - StepF10 0.08637 0.0622 Inf 1.388 0.9962
StepF6 - StepF11 0.03995 0.0622 Inf 0.642 1.0000
StepF6 - StepF12 0.22337 0.0622 Inf 3.590 0.0357
StepF6 - StepF13 0.20030 0.0622 Inf 3.220 0.1126
StepF6 - StepF14 0.11225 0.0622 Inf 1.804 0.9432
StepF6 - StepF15 0.13319 0.0622 Inf 2.141 0.7922
StepF6 - StepF16 0.31582 0.0622 Inf 5.077 0.0001
StepF6 - StepF17 0.33092 0.0622 Inf 5.319 <.0001
StepF6 - StepF18 0.59323 0.0622 Inf 9.536 <.0001
StepF7 - StepF8 -0.00766 0.0622 Inf -0.123 1.0000
StepF7 - StepF9 0.05852 0.0622 Inf 0.941 1.0000
StepF7 - StepF10 0.02499 0.0622 Inf 0.402 1.0000
StepF7 - StepF11 -0.02143 0.0622 Inf -0.345 1.0000
StepF7 - StepF12 0.16199 0.0622 Inf 2.604 0.4505
StepF7 - StepF13 0.13892 0.0622 Inf 2.233 0.7315
StepF7 - StepF14 0.05087 0.0622 Inf 0.818 1.0000
StepF7 - StepF15 0.07180 0.0622 Inf 1.154 0.9996
StepF7 - StepF16 0.25444 0.0622 Inf 4.090 0.0056
StepF7 - StepF17 0.26954 0.0622 Inf 4.333 0.0020
StepF7 - StepF18 0.53185 0.0622 Inf 8.549 <.0001
StepF8 - StepF9 0.06618 0.0622 Inf 1.064 0.9999
StepF8 - StepF10 0.03265 0.0622 Inf 0.525 1.0000
StepF8 - StepF11 -0.01378 0.0622 Inf -0.221 1.0000
StepF8 - StepF12 0.16965 0.0622 Inf 2.727 0.3613
StepF8 - StepF13 0.14658 0.0622 Inf 2.356 0.6415
StepF8 - StepF14 0.05853 0.0622 Inf 0.941 1.0000
StepF8 - StepF15 0.07946 0.0622 Inf 1.277 0.9986
StepF8 - StepF16 0.26210 0.0622 Inf 4.213 0.0033
StepF8 - StepF17 0.27720 0.0622 Inf 4.456 0.0012
StepF8 - StepF18 0.53951 0.0622 Inf 8.672 <.0001
StepF9 - StepF10 -0.03354 0.0622 Inf -0.539 1.0000
StepF9 - StepF11 -0.07996 0.0622 Inf -1.285 0.9985
StepF9 - StepF12 0.10347 0.0622 Inf 1.663 0.9733
StepF9 - StepF13 0.08040 0.0622 Inf 1.292 0.9984
StepF9 - StepF14 -0.00766 0.0622 Inf -0.123 1.0000
StepF9 - StepF15 0.01328 0.0622 Inf 0.213 1.0000
StepF9 - StepF16 0.19592 0.0622 Inf 3.149 0.1366
StepF9 - StepF17 0.21101 0.0622 Inf 3.392 0.0679
StepF9 - StepF18 0.47333 0.0622 Inf 7.608 <.0001
StepF10 - StepF11 -0.04642 0.0622 Inf -0.746 1.0000
StepF10 - StepF12 0.13700 0.0622 Inf 2.202 0.7526
StepF10 - StepF13 0.11393 0.0622 Inf 1.831 0.9354
StepF10 - StepF14 0.02588 0.0622 Inf 0.416 1.0000
StepF10 - StepF15 0.04682 0.0622 Inf 0.753 1.0000
StepF10 - StepF16 0.22945 0.0622 Inf 3.688 0.0255
StepF10 - StepF17 0.24455 0.0622 Inf 3.931 0.0104
StepF10 - StepF18 0.50686 0.0622 Inf 8.147 <.0001
StepF11 - StepF12 0.18343 0.0622 Inf 2.948 0.2259
StepF11 - StepF13 0.16036 0.0622 Inf 2.578 0.4704
StepF11 - StepF14 0.07230 0.0622 Inf 1.162 0.9996
StepF11 - StepF15 0.09324 0.0622 Inf 1.499 0.9909
StepF11 - StepF16 0.27588 0.0622 Inf 4.434 0.0013
StepF11 - StepF17 0.29097 0.0622 Inf 4.677 0.0004
StepF11 - StepF18 0.55328 0.0622 Inf 8.893 <.0001
StepF12 - StepF13 -0.02307 0.0622 Inf -0.371 1.0000
StepF12 - StepF14 -0.11112 0.0622 Inf -1.786 0.9480
StepF12 - StepF15 -0.09019 0.0622 Inf -1.450 0.9937
StepF12 - StepF16 0.09245 0.0622 Inf 1.486 0.9917
StepF12 - StepF17 0.10755 0.0622 Inf 1.729 0.9614
StepF12 - StepF18 0.36986 0.0622 Inf 5.945 <.0001
StepF13 - StepF14 -0.08805 0.0622 Inf -1.415 0.9952
StepF13 - StepF15 -0.06712 0.0622 Inf -1.079 0.9998
StepF13 - StepF16 0.11552 0.0622 Inf 1.857 0.9274
StepF13 - StepF17 0.13062 0.0622 Inf 2.100 0.8170
StepF13 - StepF18 0.39293 0.0622 Inf 6.316 <.0001
StepF14 - StepF15 0.02094 0.0622 Inf 0.337 1.0000
StepF14 - StepF16 0.20357 0.0622 Inf 3.272 0.0969
StepF14 - StepF17 0.21867 0.0622 Inf 3.515 0.0459
StepF14 - StepF18 0.48098 0.0622 Inf 7.731 <.0001
StepF15 - StepF16 0.18264 0.0622 Inf 2.936 0.2326
StepF15 - StepF17 0.19773 0.0622 Inf 3.178 0.1262
StepF15 - StepF18 0.46005 0.0622 Inf 7.395 <.0001
StepF16 - StepF17 0.01510 0.0622 Inf 0.243 1.0000
StepF16 - StepF18 0.27741 0.0622 Inf 4.459 0.0011
StepF17 - StepF18 0.26231 0.0622 Inf 4.216 0.0033
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.21381 0.0622 Inf -3.437 0.0590
StepF1 - StepF3 -0.14736 0.0622 Inf -2.369 0.6320
StepF1 - StepF4 -0.02536 0.0622 Inf -0.408 1.0000
StepF1 - StepF5 0.12653 0.0622 Inf 2.034 0.8530
StepF1 - StepF6 0.01057 0.0622 Inf 0.170 1.0000
StepF1 - StepF7 0.07195 0.0622 Inf 1.156 0.9996
StepF1 - StepF8 0.06429 0.0622 Inf 1.033 0.9999
StepF1 - StepF9 0.13047 0.0622 Inf 2.097 0.8184
StepF1 - StepF10 0.09693 0.0622 Inf 1.558 0.9862
StepF1 - StepF11 0.05051 0.0622 Inf 0.812 1.0000
StepF1 - StepF12 0.23394 0.0622 Inf 3.760 0.0197
StepF1 - StepF13 0.21087 0.0622 Inf 3.390 0.0683
StepF1 - StepF14 0.12281 0.0622 Inf 1.974 0.8819
StepF1 - StepF15 0.14375 0.0622 Inf 2.311 0.6757
StepF1 - StepF16 0.32639 0.0622 Inf 5.246 <.0001
StepF1 - StepF17 0.34148 0.0622 Inf 5.489 <.0001
StepF1 - StepF18 0.60380 0.0622 Inf 9.705 <.0001
StepF2 - StepF3 0.06645 0.0622 Inf 1.068 0.9999
StepF2 - StepF4 0.18844 0.0622 Inf 3.029 0.1861
StepF2 - StepF5 0.34033 0.0622 Inf 5.471 <.0001
StepF2 - StepF6 0.22437 0.0622 Inf 3.607 0.0338
StepF2 - StepF7 0.28575 0.0622 Inf 4.593 0.0006
StepF2 - StepF8 0.27809 0.0622 Inf 4.470 0.0011
StepF2 - StepF9 0.34428 0.0622 Inf 5.534 <.0001
StepF2 - StepF10 0.31074 0.0622 Inf 4.995 0.0001
StepF2 - StepF11 0.26432 0.0622 Inf 4.249 0.0029
StepF2 - StepF12 0.44774 0.0622 Inf 7.197 <.0001
StepF2 - StepF13 0.42468 0.0622 Inf 6.826 <.0001
StepF2 - StepF14 0.33662 0.0622 Inf 5.411 <.0001
StepF2 - StepF15 0.35756 0.0622 Inf 5.747 <.0001
StepF2 - StepF16 0.54019 0.0622 Inf 8.683 <.0001
StepF2 - StepF17 0.55529 0.0622 Inf 8.926 <.0001
StepF2 - StepF18 0.81760 0.0622 Inf 13.142 <.0001
StepF3 - StepF4 0.12200 0.0622 Inf 1.961 0.8877
StepF3 - StepF5 0.27389 0.0622 Inf 4.402 0.0015
StepF3 - StepF6 0.15793 0.0622 Inf 2.539 0.5004
StepF3 - StepF7 0.21931 0.0622 Inf 3.525 0.0444
StepF3 - StepF8 0.21165 0.0622 Inf 3.402 0.0658
StepF3 - StepF9 0.27783 0.0622 Inf 4.466 0.0011
StepF3 - StepF10 0.24430 0.0622 Inf 3.927 0.0106
StepF3 - StepF11 0.19787 0.0622 Inf 3.181 0.1254
StepF3 - StepF12 0.38130 0.0622 Inf 6.129 <.0001
StepF3 - StepF13 0.35823 0.0622 Inf 5.758 <.0001
StepF3 - StepF14 0.27018 0.0622 Inf 4.343 0.0019
StepF3 - StepF15 0.29111 0.0622 Inf 4.679 0.0004
StepF3 - StepF16 0.47375 0.0622 Inf 7.615 <.0001
StepF3 - StepF17 0.48885 0.0622 Inf 7.858 <.0001
StepF3 - StepF18 0.75116 0.0622 Inf 12.074 <.0001
StepF4 - StepF5 0.15189 0.0622 Inf 2.441 0.5758
StepF4 - StepF6 0.03593 0.0622 Inf 0.578 1.0000
StepF4 - StepF7 0.09731 0.0622 Inf 1.564 0.9856
StepF4 - StepF8 0.08965 0.0622 Inf 1.441 0.9941
StepF4 - StepF9 0.15583 0.0622 Inf 2.505 0.5264
StepF4 - StepF10 0.12230 0.0622 Inf 1.966 0.8856
StepF4 - StepF11 0.07588 0.0622 Inf 1.220 0.9992
StepF4 - StepF12 0.25930 0.0622 Inf 4.168 0.0040
StepF4 - StepF13 0.23623 0.0622 Inf 3.797 0.0172
StepF4 - StepF14 0.14818 0.0622 Inf 2.382 0.6219
StepF4 - StepF15 0.16911 0.0622 Inf 2.718 0.3673
StepF4 - StepF16 0.35175 0.0622 Inf 5.654 <.0001
StepF4 - StepF17 0.36685 0.0622 Inf 5.897 <.0001
StepF4 - StepF18 0.62916 0.0622 Inf 10.113 <.0001
StepF5 - StepF6 -0.11596 0.0622 Inf -1.864 0.9250
StepF5 - StepF7 -0.05458 0.0622 Inf -0.877 1.0000
StepF5 - StepF8 -0.06224 0.0622 Inf -1.000 0.9999
StepF5 - StepF9 0.00394 0.0622 Inf 0.063 1.0000
StepF5 - StepF10 -0.02959 0.0622 Inf -0.476 1.0000
StepF5 - StepF11 -0.07602 0.0622 Inf -1.222 0.9992
StepF5 - StepF12 0.10741 0.0622 Inf 1.727 0.9618
StepF5 - StepF13 0.08434 0.0622 Inf 1.356 0.9971
StepF5 - StepF14 -0.00371 0.0622 Inf -0.060 1.0000
StepF5 - StepF15 0.01722 0.0622 Inf 0.277 1.0000
StepF5 - StepF16 0.19986 0.0622 Inf 3.213 0.1148
StepF5 - StepF17 0.21496 0.0622 Inf 3.455 0.0557
StepF5 - StepF18 0.47727 0.0622 Inf 7.672 <.0001
StepF6 - StepF7 0.06138 0.0622 Inf 0.987 1.0000
StepF6 - StepF8 0.05372 0.0622 Inf 0.864 1.0000
StepF6 - StepF9 0.11990 0.0622 Inf 1.927 0.9018
StepF6 - StepF10 0.08637 0.0622 Inf 1.388 0.9962
StepF6 - StepF11 0.03995 0.0622 Inf 0.642 1.0000
StepF6 - StepF12 0.22337 0.0622 Inf 3.590 0.0357
StepF6 - StepF13 0.20030 0.0622 Inf 3.220 0.1126
StepF6 - StepF14 0.11225 0.0622 Inf 1.804 0.9432
StepF6 - StepF15 0.13319 0.0622 Inf 2.141 0.7922
StepF6 - StepF16 0.31582 0.0622 Inf 5.077 0.0001
StepF6 - StepF17 0.33092 0.0622 Inf 5.319 <.0001
StepF6 - StepF18 0.59323 0.0622 Inf 9.536 <.0001
StepF7 - StepF8 -0.00766 0.0622 Inf -0.123 1.0000
StepF7 - StepF9 0.05852 0.0622 Inf 0.941 1.0000
StepF7 - StepF10 0.02499 0.0622 Inf 0.402 1.0000
StepF7 - StepF11 -0.02143 0.0622 Inf -0.345 1.0000
StepF7 - StepF12 0.16199 0.0622 Inf 2.604 0.4505
StepF7 - StepF13 0.13892 0.0622 Inf 2.233 0.7315
StepF7 - StepF14 0.05087 0.0622 Inf 0.818 1.0000
StepF7 - StepF15 0.07180 0.0622 Inf 1.154 0.9996
StepF7 - StepF16 0.25444 0.0622 Inf 4.090 0.0056
StepF7 - StepF17 0.26954 0.0622 Inf 4.333 0.0020
StepF7 - StepF18 0.53185 0.0622 Inf 8.549 <.0001
StepF8 - StepF9 0.06618 0.0622 Inf 1.064 0.9999
StepF8 - StepF10 0.03265 0.0622 Inf 0.525 1.0000
StepF8 - StepF11 -0.01378 0.0622 Inf -0.221 1.0000
StepF8 - StepF12 0.16965 0.0622 Inf 2.727 0.3613
StepF8 - StepF13 0.14658 0.0622 Inf 2.356 0.6415
StepF8 - StepF14 0.05853 0.0622 Inf 0.941 1.0000
StepF8 - StepF15 0.07946 0.0622 Inf 1.277 0.9986
StepF8 - StepF16 0.26210 0.0622 Inf 4.213 0.0033
StepF8 - StepF17 0.27720 0.0622 Inf 4.456 0.0012
StepF8 - StepF18 0.53951 0.0622 Inf 8.672 <.0001
StepF9 - StepF10 -0.03354 0.0622 Inf -0.539 1.0000
StepF9 - StepF11 -0.07996 0.0622 Inf -1.285 0.9985
StepF9 - StepF12 0.10347 0.0622 Inf 1.663 0.9733
StepF9 - StepF13 0.08040 0.0622 Inf 1.292 0.9984
StepF9 - StepF14 -0.00766 0.0622 Inf -0.123 1.0000
StepF9 - StepF15 0.01328 0.0622 Inf 0.213 1.0000
StepF9 - StepF16 0.19592 0.0622 Inf 3.149 0.1366
StepF9 - StepF17 0.21101 0.0622 Inf 3.392 0.0679
StepF9 - StepF18 0.47333 0.0622 Inf 7.608 <.0001
StepF10 - StepF11 -0.04642 0.0622 Inf -0.746 1.0000
StepF10 - StepF12 0.13700 0.0622 Inf 2.202 0.7526
StepF10 - StepF13 0.11393 0.0622 Inf 1.831 0.9354
StepF10 - StepF14 0.02588 0.0622 Inf 0.416 1.0000
StepF10 - StepF15 0.04682 0.0622 Inf 0.753 1.0000
StepF10 - StepF16 0.22945 0.0622 Inf 3.688 0.0255
StepF10 - StepF17 0.24455 0.0622 Inf 3.931 0.0104
StepF10 - StepF18 0.50686 0.0622 Inf 8.147 <.0001
StepF11 - StepF12 0.18343 0.0622 Inf 2.948 0.2259
StepF11 - StepF13 0.16036 0.0622 Inf 2.578 0.4704
StepF11 - StepF14 0.07230 0.0622 Inf 1.162 0.9996
StepF11 - StepF15 0.09324 0.0622 Inf 1.499 0.9909
StepF11 - StepF16 0.27588 0.0622 Inf 4.434 0.0013
StepF11 - StepF17 0.29097 0.0622 Inf 4.677 0.0004
StepF11 - StepF18 0.55328 0.0622 Inf 8.893 <.0001
StepF12 - StepF13 -0.02307 0.0622 Inf -0.371 1.0000
StepF12 - StepF14 -0.11112 0.0622 Inf -1.786 0.9480
StepF12 - StepF15 -0.09019 0.0622 Inf -1.450 0.9937
StepF12 - StepF16 0.09245 0.0622 Inf 1.486 0.9917
StepF12 - StepF17 0.10755 0.0622 Inf 1.729 0.9614
StepF12 - StepF18 0.36986 0.0622 Inf 5.945 <.0001
StepF13 - StepF14 -0.08805 0.0622 Inf -1.415 0.9952
StepF13 - StepF15 -0.06712 0.0622 Inf -1.079 0.9998
StepF13 - StepF16 0.11552 0.0622 Inf 1.857 0.9274
StepF13 - StepF17 0.13062 0.0622 Inf 2.100 0.8170
StepF13 - StepF18 0.39293 0.0622 Inf 6.316 <.0001
StepF14 - StepF15 0.02094 0.0622 Inf 0.337 1.0000
StepF14 - StepF16 0.20357 0.0622 Inf 3.272 0.0969
StepF14 - StepF17 0.21867 0.0622 Inf 3.515 0.0459
StepF14 - StepF18 0.48098 0.0622 Inf 7.731 <.0001
StepF15 - StepF16 0.18264 0.0622 Inf 2.936 0.2326
StepF15 - StepF17 0.19773 0.0622 Inf 3.178 0.1262
StepF15 - StepF18 0.46005 0.0622 Inf 7.395 <.0001
StepF16 - StepF17 0.01510 0.0622 Inf 0.243 1.0000
StepF16 - StepF18 0.27741 0.0622 Inf 4.459 0.0011
StepF17 - StepF18 0.26231 0.0622 Inf 4.216 0.0033
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.21381 0.0622 Inf 3.437 0.0094
StepF3 - StepF2 -0.06645 0.0622 Inf -1.068 1.0000
StepF4 - StepF3 -0.12200 0.0622 Inf -1.961 0.5986
StepF5 - StepF4 -0.15189 0.0622 Inf -2.441 0.1901
StepF6 - StepF5 0.11596 0.0622 Inf 1.864 0.6856
StepF7 - StepF6 -0.06138 0.0622 Inf -0.987 1.0000
StepF8 - StepF7 0.00766 0.0622 Inf 0.123 1.0000
StepF9 - StepF8 -0.06618 0.0622 Inf -1.064 1.0000
StepF10 - StepF9 0.03354 0.0622 Inf 0.539 1.0000
StepF11 - StepF10 0.04642 0.0622 Inf 0.746 1.0000
StepF12 - StepF11 -0.18343 0.0622 Inf -2.948 0.0479
StepF13 - StepF12 0.02307 0.0622 Inf 0.371 1.0000
StepF14 - StepF13 0.08805 0.0622 Inf 1.415 1.0000
StepF15 - StepF14 -0.02094 0.0622 Inf -0.337 1.0000
StepF16 - StepF15 -0.18264 0.0622 Inf -2.936 0.0479
StepF17 - StepF16 -0.01510 0.0622 Inf -0.243 1.0000
StepF18 - StepF17 -0.26231 0.0622 Inf -4.216 0.0004
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.21381 0.0622 Inf 3.437 0.0094
StepF3 - StepF2 -0.06645 0.0622 Inf -1.068 1.0000
StepF4 - StepF3 -0.12200 0.0622 Inf -1.961 0.5986
StepF5 - StepF4 -0.15189 0.0622 Inf -2.441 0.1901
StepF6 - StepF5 0.11596 0.0622 Inf 1.864 0.6856
StepF7 - StepF6 -0.06138 0.0622 Inf -0.987 1.0000
StepF8 - StepF7 0.00766 0.0622 Inf 0.123 1.0000
StepF9 - StepF8 -0.06618 0.0622 Inf -1.064 1.0000
StepF10 - StepF9 0.03354 0.0622 Inf 0.539 1.0000
StepF11 - StepF10 0.04642 0.0622 Inf 0.746 1.0000
StepF12 - StepF11 -0.18343 0.0622 Inf -2.948 0.0479
StepF13 - StepF12 0.02307 0.0622 Inf 0.371 1.0000
StepF14 - StepF13 0.08805 0.0622 Inf 1.415 1.0000
StepF15 - StepF14 -0.02094 0.0622 Inf -0.337 1.0000
StepF16 - StepF15 -0.18264 0.0622 Inf -2.936 0.0479
StepF17 - StepF16 -0.01510 0.0622 Inf -0.243 1.0000
StepF18 - StepF17 -0.26231 0.0622 Inf -4.216 0.0004
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests # Block 5
.report_step_test(sw_b5_6, "5", "6 steps")
==============================
TEST | Block 5 | 6 steps | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 17.8923 5 0.003084 **
Accuracy 0.5532 1 0.457024
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.629 0.0457 Inf 0.540 0.719
2 0.592 0.0457 Inf 0.502 0.682
3 0.630 0.0457 Inf 0.540 0.719
4 0.611 0.0457 Inf 0.521 0.700
5 0.563 0.0457 Inf 0.473 0.653
6 0.559 0.0457 Inf 0.470 0.649
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.616 0.0459 Inf 0.526 0.706
2 0.579 0.0459 Inf 0.489 0.669
3 0.617 0.0459 Inf 0.527 0.707
4 0.598 0.0459 Inf 0.508 0.688
5 0.550 0.0459 Inf 0.460 0.640
6 0.546 0.0459 Inf 0.456 0.636
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.037257 0.0234 Inf 1.591 0.6046
StepF1 - StepF3 -0.000418 0.0234 Inf -0.018 1.0000
StepF1 - StepF4 0.018617 0.0234 Inf 0.795 0.9685
StepF1 - StepF5 0.066239 0.0234 Inf 2.829 0.0530
StepF1 - StepF6 0.070104 0.0234 Inf 2.994 0.0329
StepF2 - StepF3 -0.037674 0.0234 Inf -1.609 0.5927
StepF2 - StepF4 -0.018639 0.0234 Inf -0.796 0.9683
StepF2 - StepF5 0.028983 0.0234 Inf 1.238 0.8184
StepF2 - StepF6 0.032848 0.0234 Inf 1.403 0.7255
StepF3 - StepF4 0.019035 0.0234 Inf 0.813 0.9653
StepF3 - StepF5 0.066657 0.0234 Inf 2.846 0.0505
StepF3 - StepF6 0.070522 0.0234 Inf 3.012 0.0312
StepF4 - StepF5 0.047622 0.0234 Inf 2.034 0.3231
StepF4 - StepF6 0.051487 0.0234 Inf 2.199 0.2382
StepF5 - StepF6 0.003865 0.0234 Inf 0.165 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.037257 0.0234 Inf 1.591 0.6046
StepF1 - StepF3 -0.000418 0.0234 Inf -0.018 1.0000
StepF1 - StepF4 0.018617 0.0234 Inf 0.795 0.9685
StepF1 - StepF5 0.066239 0.0234 Inf 2.829 0.0530
StepF1 - StepF6 0.070104 0.0234 Inf 2.994 0.0329
StepF2 - StepF3 -0.037674 0.0234 Inf -1.609 0.5927
StepF2 - StepF4 -0.018639 0.0234 Inf -0.796 0.9683
StepF2 - StepF5 0.028983 0.0234 Inf 1.238 0.8184
StepF2 - StepF6 0.032848 0.0234 Inf 1.403 0.7255
StepF3 - StepF4 0.019035 0.0234 Inf 0.813 0.9653
StepF3 - StepF5 0.066657 0.0234 Inf 2.846 0.0505
StepF3 - StepF6 0.070522 0.0234 Inf 3.012 0.0312
StepF4 - StepF5 0.047622 0.0234 Inf 2.034 0.3231
StepF4 - StepF6 0.051487 0.0234 Inf 2.199 0.2382
StepF5 - StepF6 0.003865 0.0234 Inf 0.165 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.03726 0.0234 Inf -1.591 0.4306
StepF3 - StepF2 0.03767 0.0234 Inf 1.609 0.4306
StepF4 - StepF3 -0.01904 0.0234 Inf -0.813 0.8326
StepF5 - StepF4 -0.04762 0.0234 Inf -2.034 0.2100
StepF6 - StepF5 -0.00386 0.0234 Inf -0.165 0.8689
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.03726 0.0234 Inf -1.591 0.4306
StepF3 - StepF2 0.03767 0.0234 Inf 1.609 0.4306
StepF4 - StepF3 -0.01904 0.0234 Inf -0.813 0.8326
StepF5 - StepF4 -0.04762 0.0234 Inf -2.034 0.2100
StepF6 - StepF5 -0.00386 0.0234 Inf -0.165 0.8689
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests
==============================
TEST | Block 5 | 6 steps | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 52.4900 5 4.28e-10 ***
Accuracy 0.8166 1 0.3662
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.632 0.0569 Inf 0.521 0.744
2 0.741 0.0569 Inf 0.629 0.853
3 0.646 0.0569 Inf 0.534 0.757
4 0.672 0.0569 Inf 0.560 0.783
5 0.589 0.0569 Inf 0.478 0.701
6 0.589 0.0569 Inf 0.477 0.700
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.616 0.0571 Inf 0.504 0.728
2 0.724 0.0571 Inf 0.613 0.836
3 0.629 0.0571 Inf 0.517 0.741
4 0.655 0.0571 Inf 0.543 0.767
5 0.573 0.0571 Inf 0.461 0.685
6 0.572 0.0571 Inf 0.460 0.684
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.108740 0.0249 Inf -4.360 0.0002
StepF1 - StepF3 -0.013450 0.0249 Inf -0.539 0.9946
StepF1 - StepF4 -0.039309 0.0249 Inf -1.576 0.6143
StepF1 - StepF5 0.042802 0.0249 Inf 1.716 0.5208
StepF1 - StepF6 0.043406 0.0249 Inf 1.741 0.5047
StepF2 - StepF3 0.095291 0.0249 Inf 3.821 0.0018
StepF2 - StepF4 0.069432 0.0249 Inf 2.784 0.0600
StepF2 - StepF5 0.151543 0.0249 Inf 6.077 <.0001
StepF2 - StepF6 0.152147 0.0249 Inf 6.101 <.0001
StepF3 - StepF4 -0.025859 0.0249 Inf -1.037 0.9056
StepF3 - StepF5 0.056252 0.0249 Inf 2.256 0.2125
StepF3 - StepF6 0.056856 0.0249 Inf 2.280 0.2022
StepF4 - StepF5 0.082111 0.0249 Inf 3.293 0.0127
StepF4 - StepF6 0.082715 0.0249 Inf 3.317 0.0117
StepF5 - StepF6 0.000604 0.0249 Inf 0.024 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.108740 0.0249 Inf -4.360 0.0002
StepF1 - StepF3 -0.013450 0.0249 Inf -0.539 0.9946
StepF1 - StepF4 -0.039309 0.0249 Inf -1.576 0.6143
StepF1 - StepF5 0.042802 0.0249 Inf 1.716 0.5208
StepF1 - StepF6 0.043406 0.0249 Inf 1.741 0.5047
StepF2 - StepF3 0.095291 0.0249 Inf 3.821 0.0018
StepF2 - StepF4 0.069432 0.0249 Inf 2.784 0.0600
StepF2 - StepF5 0.151543 0.0249 Inf 6.077 <.0001
StepF2 - StepF6 0.152147 0.0249 Inf 6.101 <.0001
StepF3 - StepF4 -0.025859 0.0249 Inf -1.037 0.9056
StepF3 - StepF5 0.056252 0.0249 Inf 2.256 0.2125
StepF3 - StepF6 0.056856 0.0249 Inf 2.280 0.2022
StepF4 - StepF5 0.082111 0.0249 Inf 3.293 0.0127
StepF4 - StepF6 0.082715 0.0249 Inf 3.317 0.0117
StepF5 - StepF6 0.000604 0.0249 Inf 0.024 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.108740 0.0249 Inf 4.360 0.0001
StepF3 - StepF2 -0.095291 0.0249 Inf -3.821 0.0005
StepF4 - StepF3 0.025859 0.0249 Inf 1.037 0.5995
StepF5 - StepF4 -0.082111 0.0249 Inf -3.293 0.0030
StepF6 - StepF5 -0.000604 0.0249 Inf -0.024 0.9807
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.108740 0.0249 Inf 4.360 0.0001
StepF3 - StepF2 -0.095291 0.0249 Inf -3.821 0.0005
StepF4 - StepF3 0.025859 0.0249 Inf 1.037 0.5995
StepF5 - StepF4 -0.082111 0.0249 Inf -3.293 0.0030
StepF6 - StepF5 -0.000604 0.0249 Inf -0.024 0.9807
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests
==============================
TEST | Block 5 | 6 steps | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 46.8370 5 6.133e-09 ***
Accuracy 0.8531 1 0.3557
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.26 0.121 Inf 1.018 1.49
2 1.46 0.121 Inf 1.223 1.70
3 1.41 0.121 Inf 1.172 1.65
4 1.35 0.121 Inf 1.113 1.59
5 1.24 0.121 Inf 0.998 1.47
6 1.19 0.121 Inf 0.948 1.42
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.22 0.122 Inf 0.982 1.46
2 1.43 0.122 Inf 1.188 1.66
3 1.37 0.122 Inf 1.136 1.61
4 1.32 0.122 Inf 1.077 1.55
5 1.20 0.122 Inf 0.962 1.44
6 1.15 0.122 Inf 0.913 1.39
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.2055 0.0498 Inf -4.129 0.0005
StepF1 - StepF3 -0.1536 0.0498 Inf -3.086 0.0248
StepF1 - StepF4 -0.0948 0.0498 Inf -1.906 0.3986
StepF1 - StepF5 0.0205 0.0498 Inf 0.411 0.9985
StepF1 - StepF6 0.0695 0.0498 Inf 1.397 0.7286
StepF2 - StepF3 0.0519 0.0498 Inf 1.043 0.9032
StepF2 - StepF4 0.1107 0.0498 Inf 2.224 0.2266
StepF2 - StepF5 0.2259 0.0498 Inf 4.541 0.0001
StepF2 - StepF6 0.2750 0.0498 Inf 5.527 <.0001
StepF3 - StepF4 0.0587 0.0498 Inf 1.180 0.8464
StepF3 - StepF5 0.1740 0.0498 Inf 3.497 0.0063
StepF3 - StepF6 0.2231 0.0498 Inf 4.484 0.0001
StepF4 - StepF5 0.1153 0.0498 Inf 2.317 0.1870
StepF4 - StepF6 0.1644 0.0498 Inf 3.303 0.0123
StepF5 - StepF6 0.0491 0.0498 Inf 0.986 0.9225
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.2055 0.0498 Inf -4.129 0.0005
StepF1 - StepF3 -0.1536 0.0498 Inf -3.086 0.0248
StepF1 - StepF4 -0.0948 0.0498 Inf -1.906 0.3986
StepF1 - StepF5 0.0205 0.0498 Inf 0.411 0.9985
StepF1 - StepF6 0.0695 0.0498 Inf 1.397 0.7286
StepF2 - StepF3 0.0519 0.0498 Inf 1.043 0.9032
StepF2 - StepF4 0.1107 0.0498 Inf 2.224 0.2266
StepF2 - StepF5 0.2259 0.0498 Inf 4.541 0.0001
StepF2 - StepF6 0.2750 0.0498 Inf 5.527 <.0001
StepF3 - StepF4 0.0587 0.0498 Inf 1.180 0.8464
StepF3 - StepF5 0.1740 0.0498 Inf 3.497 0.0063
StepF3 - StepF6 0.2231 0.0498 Inf 4.484 0.0001
StepF4 - StepF5 0.1153 0.0498 Inf 2.317 0.1870
StepF4 - StepF6 0.1644 0.0498 Inf 3.303 0.0123
StepF5 - StepF6 0.0491 0.0498 Inf 0.986 0.9225
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 6 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2055 0.0498 Inf 4.129 0.0002
StepF3 - StepF2 -0.0519 0.0498 Inf -1.043 0.7135
StepF4 - StepF3 -0.0587 0.0498 Inf -1.180 0.7135
StepF5 - StepF4 -0.1153 0.0498 Inf -2.317 0.0820
StepF6 - StepF5 -0.0491 0.0498 Inf -0.986 0.7135
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2055 0.0498 Inf 4.129 0.0002
StepF3 - StepF2 -0.0519 0.0498 Inf -1.043 0.7135
StepF4 - StepF3 -0.0587 0.0498 Inf -1.180 0.7135
StepF5 - StepF4 -0.1153 0.0498 Inf -2.317 0.0820
StepF6 - StepF5 -0.0491 0.0498 Inf -0.986 0.7135
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 5 tests .report_step_test(sw_b5_12, "5", "12 steps")
==============================
TEST | Block 5 | 12 steps | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 84.4825 11 1.993e-13 ***
Accuracy 0.6423 1 0.4229
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.647 0.0514 Inf 0.546 0.748
2 0.633 0.0514 Inf 0.532 0.734
3 0.685 0.0514 Inf 0.585 0.786
4 0.581 0.0514 Inf 0.480 0.681
5 0.573 0.0514 Inf 0.473 0.674
6 0.602 0.0514 Inf 0.501 0.703
7 0.605 0.0514 Inf 0.504 0.706
8 0.585 0.0514 Inf 0.484 0.685
9 0.512 0.0514 Inf 0.411 0.613
10 0.575 0.0514 Inf 0.474 0.675
11 0.616 0.0514 Inf 0.515 0.717
12 0.535 0.0514 Inf 0.434 0.636
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.635 0.0516 Inf 0.534 0.737
2 0.622 0.0516 Inf 0.520 0.723
3 0.674 0.0516 Inf 0.573 0.775
4 0.569 0.0516 Inf 0.468 0.671
5 0.562 0.0516 Inf 0.461 0.663
6 0.591 0.0516 Inf 0.489 0.692
7 0.594 0.0516 Inf 0.493 0.695
8 0.573 0.0516 Inf 0.472 0.674
9 0.501 0.0516 Inf 0.400 0.602
10 0.563 0.0516 Inf 0.462 0.665
11 0.605 0.0516 Inf 0.504 0.706
12 0.524 0.0516 Inf 0.423 0.625
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.01389 0.0241 Inf 0.576 1.0000
StepF1 - StepF3 -0.03861 0.0241 Inf -1.603 0.9087
StepF1 - StepF4 0.06607 0.0241 Inf 2.742 0.2055
StepF1 - StepF5 0.07326 0.0241 Inf 3.040 0.0971
StepF1 - StepF6 0.04483 0.0241 Inf 1.861 0.7838
StepF1 - StepF7 0.04161 0.0241 Inf 1.727 0.8562
StepF1 - StepF8 0.06216 0.0241 Inf 2.580 0.2912
StepF1 - StepF9 0.13466 0.0241 Inf 5.589 <.0001
StepF1 - StepF10 0.07206 0.0241 Inf 2.991 0.1111
StepF1 - StepF11 0.03056 0.0241 Inf 1.268 0.9830
StepF1 - StepF12 0.11166 0.0241 Inf 4.634 0.0002
StepF2 - StepF3 -0.05250 0.0241 Inf -2.179 0.5651
StepF2 - StepF4 0.05219 0.0241 Inf 2.166 0.5746
StepF2 - StepF5 0.05937 0.0241 Inf 2.464 0.3629
StepF2 - StepF6 0.03094 0.0241 Inf 1.284 0.9812
StepF2 - StepF7 0.02772 0.0241 Inf 1.150 0.9923
StepF2 - StepF8 0.04827 0.0241 Inf 2.003 0.6914
StepF2 - StepF9 0.12078 0.0241 Inf 5.013 <.0001
StepF2 - StepF10 0.05817 0.0241 Inf 2.414 0.3960
StepF2 - StepF11 0.01667 0.0241 Inf 0.692 0.9999
StepF2 - StepF12 0.09778 0.0241 Inf 4.058 0.0029
StepF3 - StepF4 0.10469 0.0241 Inf 4.345 0.0009
StepF3 - StepF5 0.11187 0.0241 Inf 4.643 0.0002
StepF3 - StepF6 0.08344 0.0241 Inf 3.463 0.0267
StepF3 - StepF7 0.08022 0.0241 Inf 3.329 0.0413
StepF3 - StepF8 0.10077 0.0241 Inf 4.182 0.0017
StepF3 - StepF9 0.17328 0.0241 Inf 7.192 <.0001
StepF3 - StepF10 0.11067 0.0241 Inf 4.593 0.0003
StepF3 - StepF11 0.06917 0.0241 Inf 2.871 0.1513
StepF3 - StepF12 0.15028 0.0241 Inf 6.237 <.0001
StepF4 - StepF5 0.00718 0.0241 Inf 0.298 1.0000
StepF4 - StepF6 -0.02125 0.0241 Inf -0.882 0.9993
StepF4 - StepF7 -0.02447 0.0241 Inf -1.016 0.9974
StepF4 - StepF8 -0.00392 0.0241 Inf -0.163 1.0000
StepF4 - StepF9 0.06859 0.0241 Inf 2.847 0.1606
StepF4 - StepF10 0.00599 0.0241 Inf 0.248 1.0000
StepF4 - StepF11 -0.03551 0.0241 Inf -1.474 0.9478
StepF4 - StepF12 0.04559 0.0241 Inf 1.892 0.7646
StepF5 - StepF6 -0.02843 0.0241 Inf -1.180 0.9905
StepF5 - StepF7 -0.03165 0.0241 Inf -1.314 0.9776
StepF5 - StepF8 -0.01110 0.0241 Inf -0.461 1.0000
StepF5 - StepF9 0.06141 0.0241 Inf 2.549 0.3096
StepF5 - StepF10 -0.00119 0.0241 Inf -0.050 1.0000
StepF5 - StepF11 -0.04270 0.0241 Inf -1.772 0.8335
StepF5 - StepF12 0.03841 0.0241 Inf 1.594 0.9117
StepF6 - StepF7 -0.00322 0.0241 Inf -0.134 1.0000
StepF6 - StepF8 0.01733 0.0241 Inf 0.719 0.9999
StepF6 - StepF9 0.08984 0.0241 Inf 3.728 0.0105
StepF6 - StepF10 0.02723 0.0241 Inf 1.130 0.9934
StepF6 - StepF11 -0.01427 0.0241 Inf -0.592 1.0000
StepF6 - StepF12 0.06683 0.0241 Inf 2.774 0.1912
StepF7 - StepF8 0.02055 0.0241 Inf 0.853 0.9995
StepF7 - StepF9 0.09306 0.0241 Inf 3.862 0.0063
StepF7 - StepF10 0.03045 0.0241 Inf 1.264 0.9834
StepF7 - StepF11 -0.01105 0.0241 Inf -0.458 1.0000
StepF7 - StepF12 0.07006 0.0241 Inf 2.908 0.1380
StepF8 - StepF9 0.07251 0.0241 Inf 3.009 0.1057
StepF8 - StepF10 0.00991 0.0241 Inf 0.411 1.0000
StepF8 - StepF11 -0.03159 0.0241 Inf -1.311 0.9779
StepF8 - StepF12 0.04951 0.0241 Inf 2.055 0.6554
StepF9 - StepF10 -0.06260 0.0241 Inf -2.598 0.2804
StepF9 - StepF11 -0.10410 0.0241 Inf -4.321 0.0009
StepF9 - StepF12 -0.02300 0.0241 Inf -0.955 0.9985
StepF10 - StepF11 -0.04150 0.0241 Inf -1.722 0.8583
StepF10 - StepF12 0.03960 0.0241 Inf 1.644 0.8929
StepF11 - StepF12 0.08110 0.0241 Inf 3.366 0.0367
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.01389 0.0241 Inf 0.576 1.0000
StepF1 - StepF3 -0.03861 0.0241 Inf -1.603 0.9087
StepF1 - StepF4 0.06607 0.0241 Inf 2.742 0.2055
StepF1 - StepF5 0.07326 0.0241 Inf 3.040 0.0971
StepF1 - StepF6 0.04483 0.0241 Inf 1.861 0.7838
StepF1 - StepF7 0.04161 0.0241 Inf 1.727 0.8562
StepF1 - StepF8 0.06216 0.0241 Inf 2.580 0.2912
StepF1 - StepF9 0.13466 0.0241 Inf 5.589 <.0001
StepF1 - StepF10 0.07206 0.0241 Inf 2.991 0.1111
StepF1 - StepF11 0.03056 0.0241 Inf 1.268 0.9830
StepF1 - StepF12 0.11166 0.0241 Inf 4.634 0.0002
StepF2 - StepF3 -0.05250 0.0241 Inf -2.179 0.5651
StepF2 - StepF4 0.05219 0.0241 Inf 2.166 0.5746
StepF2 - StepF5 0.05937 0.0241 Inf 2.464 0.3629
StepF2 - StepF6 0.03094 0.0241 Inf 1.284 0.9812
StepF2 - StepF7 0.02772 0.0241 Inf 1.150 0.9923
StepF2 - StepF8 0.04827 0.0241 Inf 2.003 0.6914
StepF2 - StepF9 0.12078 0.0241 Inf 5.013 <.0001
StepF2 - StepF10 0.05817 0.0241 Inf 2.414 0.3960
StepF2 - StepF11 0.01667 0.0241 Inf 0.692 0.9999
StepF2 - StepF12 0.09778 0.0241 Inf 4.058 0.0029
StepF3 - StepF4 0.10469 0.0241 Inf 4.345 0.0009
StepF3 - StepF5 0.11187 0.0241 Inf 4.643 0.0002
StepF3 - StepF6 0.08344 0.0241 Inf 3.463 0.0267
StepF3 - StepF7 0.08022 0.0241 Inf 3.329 0.0413
StepF3 - StepF8 0.10077 0.0241 Inf 4.182 0.0017
StepF3 - StepF9 0.17328 0.0241 Inf 7.192 <.0001
StepF3 - StepF10 0.11067 0.0241 Inf 4.593 0.0003
StepF3 - StepF11 0.06917 0.0241 Inf 2.871 0.1513
StepF3 - StepF12 0.15028 0.0241 Inf 6.237 <.0001
StepF4 - StepF5 0.00718 0.0241 Inf 0.298 1.0000
StepF4 - StepF6 -0.02125 0.0241 Inf -0.882 0.9993
StepF4 - StepF7 -0.02447 0.0241 Inf -1.016 0.9974
StepF4 - StepF8 -0.00392 0.0241 Inf -0.163 1.0000
StepF4 - StepF9 0.06859 0.0241 Inf 2.847 0.1606
StepF4 - StepF10 0.00599 0.0241 Inf 0.248 1.0000
StepF4 - StepF11 -0.03551 0.0241 Inf -1.474 0.9478
StepF4 - StepF12 0.04559 0.0241 Inf 1.892 0.7646
StepF5 - StepF6 -0.02843 0.0241 Inf -1.180 0.9905
StepF5 - StepF7 -0.03165 0.0241 Inf -1.314 0.9776
StepF5 - StepF8 -0.01110 0.0241 Inf -0.461 1.0000
StepF5 - StepF9 0.06141 0.0241 Inf 2.549 0.3096
StepF5 - StepF10 -0.00119 0.0241 Inf -0.050 1.0000
StepF5 - StepF11 -0.04270 0.0241 Inf -1.772 0.8335
StepF5 - StepF12 0.03841 0.0241 Inf 1.594 0.9117
StepF6 - StepF7 -0.00322 0.0241 Inf -0.134 1.0000
StepF6 - StepF8 0.01733 0.0241 Inf 0.719 0.9999
StepF6 - StepF9 0.08984 0.0241 Inf 3.728 0.0105
StepF6 - StepF10 0.02723 0.0241 Inf 1.130 0.9934
StepF6 - StepF11 -0.01427 0.0241 Inf -0.592 1.0000
StepF6 - StepF12 0.06683 0.0241 Inf 2.774 0.1912
StepF7 - StepF8 0.02055 0.0241 Inf 0.853 0.9995
StepF7 - StepF9 0.09306 0.0241 Inf 3.862 0.0063
StepF7 - StepF10 0.03045 0.0241 Inf 1.264 0.9834
StepF7 - StepF11 -0.01105 0.0241 Inf -0.458 1.0000
StepF7 - StepF12 0.07006 0.0241 Inf 2.908 0.1380
StepF8 - StepF9 0.07251 0.0241 Inf 3.009 0.1057
StepF8 - StepF10 0.00991 0.0241 Inf 0.411 1.0000
StepF8 - StepF11 -0.03159 0.0241 Inf -1.311 0.9779
StepF8 - StepF12 0.04951 0.0241 Inf 2.055 0.6554
StepF9 - StepF10 -0.06260 0.0241 Inf -2.598 0.2804
StepF9 - StepF11 -0.10410 0.0241 Inf -4.321 0.0009
StepF9 - StepF12 -0.02300 0.0241 Inf -0.955 0.9985
StepF10 - StepF11 -0.04150 0.0241 Inf -1.722 0.8583
StepF10 - StepF12 0.03960 0.0241 Inf 1.644 0.8929
StepF11 - StepF12 0.08110 0.0241 Inf 3.366 0.0367
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.01389 0.0241 Inf -0.576 1.0000
StepF3 - StepF2 0.05250 0.0241 Inf 2.179 0.2054
StepF4 - StepF3 -0.10469 0.0241 Inf -4.345 0.0002
StepF5 - StepF4 -0.00718 0.0241 Inf -0.298 1.0000
StepF6 - StepF5 0.02843 0.0241 Inf 1.180 1.0000
StepF7 - StepF6 0.00322 0.0241 Inf 0.134 1.0000
StepF8 - StepF7 -0.02055 0.0241 Inf -0.853 1.0000
StepF9 - StepF8 -0.07251 0.0241 Inf -3.009 0.0236
StepF10 - StepF9 0.06260 0.0241 Inf 2.598 0.0750
StepF11 - StepF10 0.04150 0.0241 Inf 1.722 0.5100
StepF12 - StepF11 -0.08110 0.0241 Inf -3.366 0.0076
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.01389 0.0241 Inf -0.576 1.0000
StepF3 - StepF2 0.05250 0.0241 Inf 2.179 0.2054
StepF4 - StepF3 -0.10469 0.0241 Inf -4.345 0.0002
StepF5 - StepF4 -0.00718 0.0241 Inf -0.298 1.0000
StepF6 - StepF5 0.02843 0.0241 Inf 1.180 1.0000
StepF7 - StepF6 0.00322 0.0241 Inf 0.134 1.0000
StepF8 - StepF7 -0.02055 0.0241 Inf -0.853 1.0000
StepF9 - StepF8 -0.07251 0.0241 Inf -3.009 0.0236
StepF10 - StepF9 0.06260 0.0241 Inf 2.598 0.0750
StepF11 - StepF10 0.04150 0.0241 Inf 1.722 0.5100
StepF12 - StepF11 -0.08110 0.0241 Inf -3.366 0.0076
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests
==============================
TEST | Block 5 | 12 steps | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 185.541 11 <2e-16 ***
Accuracy 2.564 1 0.1093
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.620 0.0594 Inf 0.504 0.737
2 0.789 0.0594 Inf 0.672 0.905
3 0.685 0.0594 Inf 0.568 0.801
4 0.683 0.0594 Inf 0.567 0.800
5 0.604 0.0594 Inf 0.488 0.721
6 0.522 0.0594 Inf 0.406 0.639
7 0.601 0.0594 Inf 0.485 0.718
8 0.632 0.0594 Inf 0.515 0.748
9 0.551 0.0594 Inf 0.434 0.667
10 0.644 0.0594 Inf 0.527 0.760
11 0.619 0.0594 Inf 0.502 0.735
12 0.549 0.0594 Inf 0.432 0.665
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.598 0.0596 Inf 0.481 0.714
2 0.766 0.0596 Inf 0.649 0.883
3 0.662 0.0596 Inf 0.545 0.779
4 0.660 0.0596 Inf 0.544 0.777
5 0.581 0.0596 Inf 0.465 0.698
6 0.500 0.0596 Inf 0.383 0.616
7 0.578 0.0596 Inf 0.462 0.695
8 0.609 0.0596 Inf 0.492 0.726
9 0.528 0.0596 Inf 0.411 0.645
10 0.621 0.0596 Inf 0.504 0.738
11 0.596 0.0596 Inf 0.479 0.713
12 0.526 0.0596 Inf 0.409 0.643
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.16822 0.0248 Inf -6.786 <.0001
StepF1 - StepF3 -0.06454 0.0248 Inf -2.603 0.2775
StepF1 - StepF4 -0.06290 0.0248 Inf -2.537 0.3165
StepF1 - StepF5 0.01615 0.0248 Inf 0.652 1.0000
StepF1 - StepF6 0.09793 0.0248 Inf 3.950 0.0045
StepF1 - StepF7 0.01918 0.0248 Inf 0.774 0.9998
StepF1 - StepF8 -0.01137 0.0248 Inf -0.458 1.0000
StepF1 - StepF9 0.06967 0.0248 Inf 2.810 0.1755
StepF1 - StepF10 -0.02338 0.0248 Inf -0.943 0.9987
StepF1 - StepF11 0.00173 0.0248 Inf 0.070 1.0000
StepF1 - StepF12 0.07136 0.0248 Inf 2.878 0.1486
StepF2 - StepF3 0.10368 0.0248 Inf 4.182 0.0017
StepF2 - StepF4 0.10532 0.0248 Inf 4.248 0.0013
StepF2 - StepF5 0.18438 0.0248 Inf 7.437 <.0001
StepF2 - StepF6 0.26615 0.0248 Inf 10.736 <.0001
StepF2 - StepF7 0.18740 0.0248 Inf 7.559 <.0001
StepF2 - StepF8 0.15686 0.0248 Inf 6.327 <.0001
StepF2 - StepF9 0.23789 0.0248 Inf 9.596 <.0001
StepF2 - StepF10 0.14485 0.0248 Inf 5.843 <.0001
StepF2 - StepF11 0.16995 0.0248 Inf 6.855 <.0001
StepF2 - StepF12 0.23958 0.0248 Inf 9.664 <.0001
StepF3 - StepF4 0.00164 0.0248 Inf 0.066 1.0000
StepF3 - StepF5 0.08069 0.0248 Inf 3.255 0.0520
StepF3 - StepF6 0.16247 0.0248 Inf 6.554 <.0001
StepF3 - StepF7 0.08372 0.0248 Inf 3.377 0.0354
StepF3 - StepF8 0.05318 0.0248 Inf 2.145 0.5900
StepF3 - StepF9 0.13421 0.0248 Inf 5.414 <.0001
StepF3 - StepF10 0.04117 0.0248 Inf 1.661 0.8860
StepF3 - StepF11 0.06627 0.0248 Inf 2.673 0.2396
StepF3 - StepF12 0.13590 0.0248 Inf 5.482 <.0001
StepF4 - StepF5 0.07905 0.0248 Inf 3.189 0.0636
StepF4 - StepF6 0.16083 0.0248 Inf 6.487 <.0001
StepF4 - StepF7 0.08208 0.0248 Inf 3.311 0.0438
StepF4 - StepF8 0.05153 0.0248 Inf 2.079 0.6382
StepF4 - StepF9 0.13257 0.0248 Inf 5.347 <.0001
StepF4 - StepF10 0.03952 0.0248 Inf 1.594 0.9116
StepF4 - StepF11 0.06463 0.0248 Inf 2.607 0.2755
StepF4 - StepF12 0.13426 0.0248 Inf 5.415 <.0001
StepF5 - StepF6 0.08178 0.0248 Inf 3.299 0.0455
StepF5 - StepF7 0.00302 0.0248 Inf 0.122 1.0000
StepF5 - StepF8 -0.02752 0.0248 Inf -1.110 0.9943
StepF5 - StepF9 0.05351 0.0248 Inf 2.159 0.5801
StepF5 - StepF10 -0.03953 0.0248 Inf -1.594 0.9116
StepF5 - StepF11 -0.01442 0.0248 Inf -0.582 1.0000
StepF5 - StepF12 0.05520 0.0248 Inf 2.227 0.5299
StepF6 - StepF7 -0.07875 0.0248 Inf -3.177 0.0659
StepF6 - StepF8 -0.10930 0.0248 Inf -4.409 0.0006
StepF6 - StepF9 -0.02826 0.0248 Inf -1.140 0.9929
StepF6 - StepF10 -0.12131 0.0248 Inf -4.893 0.0001
StepF6 - StepF11 -0.09620 0.0248 Inf -3.880 0.0059
StepF6 - StepF12 -0.02657 0.0248 Inf -1.072 0.9958
StepF7 - StepF8 -0.03054 0.0248 Inf -1.232 0.9865
StepF7 - StepF9 0.05049 0.0248 Inf 2.037 0.6682
StepF7 - StepF10 -0.04255 0.0248 Inf -1.716 0.8611
StepF7 - StepF11 -0.01745 0.0248 Inf -0.704 0.9999
StepF7 - StepF12 0.05218 0.0248 Inf 2.105 0.6193
StepF8 - StepF9 0.08103 0.0248 Inf 3.269 0.0499
StepF8 - StepF10 -0.01201 0.0248 Inf -0.484 1.0000
StepF8 - StepF11 0.01309 0.0248 Inf 0.528 1.0000
StepF8 - StepF12 0.08272 0.0248 Inf 3.337 0.0403
StepF9 - StepF10 -0.09304 0.0248 Inf -3.753 0.0096
StepF9 - StepF11 -0.06794 0.0248 Inf -2.740 0.2064
StepF9 - StepF12 0.00169 0.0248 Inf 0.068 1.0000
StepF10 - StepF11 0.02510 0.0248 Inf 1.013 0.9975
StepF10 - StepF12 0.09473 0.0248 Inf 3.821 0.0074
StepF11 - StepF12 0.06963 0.0248 Inf 2.809 0.1761
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.16822 0.0248 Inf -6.786 <.0001
StepF1 - StepF3 -0.06454 0.0248 Inf -2.603 0.2775
StepF1 - StepF4 -0.06290 0.0248 Inf -2.537 0.3165
StepF1 - StepF5 0.01615 0.0248 Inf 0.652 1.0000
StepF1 - StepF6 0.09793 0.0248 Inf 3.950 0.0045
StepF1 - StepF7 0.01918 0.0248 Inf 0.774 0.9998
StepF1 - StepF8 -0.01137 0.0248 Inf -0.458 1.0000
StepF1 - StepF9 0.06967 0.0248 Inf 2.810 0.1755
StepF1 - StepF10 -0.02338 0.0248 Inf -0.943 0.9987
StepF1 - StepF11 0.00173 0.0248 Inf 0.070 1.0000
StepF1 - StepF12 0.07136 0.0248 Inf 2.878 0.1486
StepF2 - StepF3 0.10368 0.0248 Inf 4.182 0.0017
StepF2 - StepF4 0.10532 0.0248 Inf 4.248 0.0013
StepF2 - StepF5 0.18438 0.0248 Inf 7.437 <.0001
StepF2 - StepF6 0.26615 0.0248 Inf 10.736 <.0001
StepF2 - StepF7 0.18740 0.0248 Inf 7.559 <.0001
StepF2 - StepF8 0.15686 0.0248 Inf 6.327 <.0001
StepF2 - StepF9 0.23789 0.0248 Inf 9.596 <.0001
StepF2 - StepF10 0.14485 0.0248 Inf 5.843 <.0001
StepF2 - StepF11 0.16995 0.0248 Inf 6.855 <.0001
StepF2 - StepF12 0.23958 0.0248 Inf 9.664 <.0001
StepF3 - StepF4 0.00164 0.0248 Inf 0.066 1.0000
StepF3 - StepF5 0.08069 0.0248 Inf 3.255 0.0520
StepF3 - StepF6 0.16247 0.0248 Inf 6.554 <.0001
StepF3 - StepF7 0.08372 0.0248 Inf 3.377 0.0354
StepF3 - StepF8 0.05318 0.0248 Inf 2.145 0.5900
StepF3 - StepF9 0.13421 0.0248 Inf 5.414 <.0001
StepF3 - StepF10 0.04117 0.0248 Inf 1.661 0.8860
StepF3 - StepF11 0.06627 0.0248 Inf 2.673 0.2396
StepF3 - StepF12 0.13590 0.0248 Inf 5.482 <.0001
StepF4 - StepF5 0.07905 0.0248 Inf 3.189 0.0636
StepF4 - StepF6 0.16083 0.0248 Inf 6.487 <.0001
StepF4 - StepF7 0.08208 0.0248 Inf 3.311 0.0438
StepF4 - StepF8 0.05153 0.0248 Inf 2.079 0.6382
StepF4 - StepF9 0.13257 0.0248 Inf 5.347 <.0001
StepF4 - StepF10 0.03952 0.0248 Inf 1.594 0.9116
StepF4 - StepF11 0.06463 0.0248 Inf 2.607 0.2755
StepF4 - StepF12 0.13426 0.0248 Inf 5.415 <.0001
StepF5 - StepF6 0.08178 0.0248 Inf 3.299 0.0455
StepF5 - StepF7 0.00302 0.0248 Inf 0.122 1.0000
StepF5 - StepF8 -0.02752 0.0248 Inf -1.110 0.9943
StepF5 - StepF9 0.05351 0.0248 Inf 2.159 0.5801
StepF5 - StepF10 -0.03953 0.0248 Inf -1.594 0.9116
StepF5 - StepF11 -0.01442 0.0248 Inf -0.582 1.0000
StepF5 - StepF12 0.05520 0.0248 Inf 2.227 0.5299
StepF6 - StepF7 -0.07875 0.0248 Inf -3.177 0.0659
StepF6 - StepF8 -0.10930 0.0248 Inf -4.409 0.0006
StepF6 - StepF9 -0.02826 0.0248 Inf -1.140 0.9929
StepF6 - StepF10 -0.12131 0.0248 Inf -4.893 0.0001
StepF6 - StepF11 -0.09620 0.0248 Inf -3.880 0.0059
StepF6 - StepF12 -0.02657 0.0248 Inf -1.072 0.9958
StepF7 - StepF8 -0.03054 0.0248 Inf -1.232 0.9865
StepF7 - StepF9 0.05049 0.0248 Inf 2.037 0.6682
StepF7 - StepF10 -0.04255 0.0248 Inf -1.716 0.8611
StepF7 - StepF11 -0.01745 0.0248 Inf -0.704 0.9999
StepF7 - StepF12 0.05218 0.0248 Inf 2.105 0.6193
StepF8 - StepF9 0.08103 0.0248 Inf 3.269 0.0499
StepF8 - StepF10 -0.01201 0.0248 Inf -0.484 1.0000
StepF8 - StepF11 0.01309 0.0248 Inf 0.528 1.0000
StepF8 - StepF12 0.08272 0.0248 Inf 3.337 0.0403
StepF9 - StepF10 -0.09304 0.0248 Inf -3.753 0.0096
StepF9 - StepF11 -0.06794 0.0248 Inf -2.740 0.2064
StepF9 - StepF12 0.00169 0.0248 Inf 0.068 1.0000
StepF10 - StepF11 0.02510 0.0248 Inf 1.013 0.9975
StepF10 - StepF12 0.09473 0.0248 Inf 3.821 0.0074
StepF11 - StepF12 0.06963 0.0248 Inf 2.809 0.1761
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.16822 0.0248 Inf 6.786 <.0001
StepF3 - StepF2 -0.10368 0.0248 Inf -4.182 0.0003
StepF4 - StepF3 -0.00164 0.0248 Inf -0.066 0.9472
StepF5 - StepF4 -0.07905 0.0248 Inf -3.189 0.0086
StepF6 - StepF5 -0.08178 0.0248 Inf -3.299 0.0078
StepF7 - StepF6 0.07875 0.0248 Inf 3.177 0.0086
StepF8 - StepF7 0.03054 0.0248 Inf 1.232 0.6539
StepF9 - StepF8 -0.08103 0.0248 Inf -3.269 0.0078
StepF10 - StepF9 0.09304 0.0248 Inf 3.753 0.0016
StepF11 - StepF10 -0.02510 0.0248 Inf -1.013 0.6539
StepF12 - StepF11 -0.06963 0.0248 Inf -2.809 0.0199
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.16822 0.0248 Inf 6.786 <.0001
StepF3 - StepF2 -0.10368 0.0248 Inf -4.182 0.0003
StepF4 - StepF3 -0.00164 0.0248 Inf -0.066 0.9472
StepF5 - StepF4 -0.07905 0.0248 Inf -3.189 0.0086
StepF6 - StepF5 -0.08178 0.0248 Inf -3.299 0.0078
StepF7 - StepF6 0.07875 0.0248 Inf 3.177 0.0086
StepF8 - StepF7 0.03054 0.0248 Inf 1.232 0.6539
StepF9 - StepF8 -0.08103 0.0248 Inf -3.269 0.0078
StepF10 - StepF9 0.09304 0.0248 Inf 3.753 0.0016
StepF11 - StepF10 -0.02510 0.0248 Inf -1.013 0.6539
StepF12 - StepF11 -0.06963 0.0248 Inf -2.809 0.0199
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests
==============================
TEST | Block 5 | 12 steps | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 149.6389 11 <2e-16 ***
Accuracy 0.8579 1 0.3543
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.31 0.137 Inf 1.038 1.57
2 1.56 0.137 Inf 1.295 1.83
3 1.40 0.137 Inf 1.128 1.66
4 1.25 0.137 Inf 0.986 1.52
5 1.26 0.137 Inf 0.995 1.53
6 1.24 0.137 Inf 0.967 1.50
7 1.29 0.137 Inf 1.020 1.56
8 1.21 0.137 Inf 0.944 1.48
9 1.18 0.137 Inf 0.911 1.45
10 1.24 0.137 Inf 0.968 1.50
11 1.22 0.137 Inf 0.956 1.49
12 1.13 0.137 Inf 0.859 1.40
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.28 0.137 Inf 1.013 1.55
2 1.54 0.137 Inf 1.270 1.81
3 1.37 0.137 Inf 1.103 1.64
4 1.23 0.137 Inf 0.961 1.50
5 1.24 0.137 Inf 0.970 1.51
6 1.21 0.137 Inf 0.942 1.48
7 1.26 0.137 Inf 0.994 1.53
8 1.19 0.137 Inf 0.919 1.46
9 1.15 0.137 Inf 0.886 1.42
10 1.21 0.137 Inf 0.942 1.48
11 1.20 0.137 Inf 0.931 1.47
12 1.10 0.137 Inf 0.834 1.37
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.257079 0.0433 Inf -5.939 <.0001
StepF1 - StepF3 -0.090156 0.0433 Inf -2.083 0.6354
StepF1 - StepF4 0.052115 0.0433 Inf 1.204 0.9888
StepF1 - StepF5 0.042898 0.0433 Inf 0.991 0.9979
StepF1 - StepF6 0.071171 0.0433 Inf 1.644 0.8928
StepF1 - StepF7 0.018358 0.0433 Inf 0.424 1.0000
StepF1 - StepF8 0.094084 0.0433 Inf 2.173 0.5692
StepF1 - StepF9 0.127231 0.0433 Inf 2.939 0.1273
StepF1 - StepF10 0.070430 0.0433 Inf 1.627 0.8995
StepF1 - StepF11 0.081979 0.0433 Inf 1.894 0.7635
StepF1 - StepF12 0.178834 0.0433 Inf 4.131 0.0021
StepF2 - StepF3 0.166923 0.0433 Inf 3.856 0.0065
StepF2 - StepF4 0.309194 0.0433 Inf 7.142 <.0001
StepF2 - StepF5 0.299977 0.0433 Inf 6.930 <.0001
StepF2 - StepF6 0.328250 0.0433 Inf 7.583 <.0001
StepF2 - StepF7 0.275437 0.0433 Inf 6.363 <.0001
StepF2 - StepF8 0.351163 0.0433 Inf 8.112 <.0001
StepF2 - StepF9 0.384310 0.0433 Inf 8.878 <.0001
StepF2 - StepF10 0.327509 0.0433 Inf 7.566 <.0001
StepF2 - StepF11 0.339058 0.0433 Inf 7.832 <.0001
StepF2 - StepF12 0.435913 0.0433 Inf 10.070 <.0001
StepF3 - StepF4 0.142271 0.0433 Inf 3.286 0.0472
StepF3 - StepF5 0.133054 0.0433 Inf 3.074 0.0886
StepF3 - StepF6 0.161327 0.0433 Inf 3.727 0.0105
StepF3 - StepF7 0.108514 0.0433 Inf 2.507 0.3355
StepF3 - StepF8 0.184240 0.0433 Inf 4.256 0.0013
StepF3 - StepF9 0.217387 0.0433 Inf 5.022 <.0001
StepF3 - StepF10 0.160586 0.0433 Inf 3.710 0.0112
StepF3 - StepF11 0.172135 0.0433 Inf 3.976 0.0040
StepF3 - StepF12 0.268990 0.0433 Inf 6.214 <.0001
StepF4 - StepF5 -0.009217 0.0433 Inf -0.213 1.0000
StepF4 - StepF6 0.019056 0.0433 Inf 0.440 1.0000
StepF4 - StepF7 -0.033757 0.0433 Inf -0.780 0.9998
StepF4 - StepF8 0.041969 0.0433 Inf 0.969 0.9983
StepF4 - StepF9 0.075116 0.0433 Inf 1.735 0.8521
StepF4 - StepF10 0.018315 0.0433 Inf 0.423 1.0000
StepF4 - StepF11 0.029864 0.0433 Inf 0.690 0.9999
StepF4 - StepF12 0.126719 0.0433 Inf 2.927 0.1312
StepF5 - StepF6 0.028273 0.0433 Inf 0.653 1.0000
StepF5 - StepF7 -0.024539 0.0433 Inf -0.567 1.0000
StepF5 - StepF8 0.051186 0.0433 Inf 1.182 0.9903
StepF5 - StepF9 0.084334 0.0433 Inf 1.948 0.7286
StepF5 - StepF10 0.027532 0.0433 Inf 0.636 1.0000
StepF5 - StepF11 0.039082 0.0433 Inf 0.903 0.9991
StepF5 - StepF12 0.135936 0.0433 Inf 3.140 0.0733
StepF6 - StepF7 -0.052813 0.0433 Inf -1.220 0.9875
StepF6 - StepF8 0.022913 0.0433 Inf 0.529 1.0000
StepF6 - StepF9 0.056060 0.0433 Inf 1.295 0.9799
StepF6 - StepF10 -0.000741 0.0433 Inf -0.017 1.0000
StepF6 - StepF11 0.010808 0.0433 Inf 0.250 1.0000
StepF6 - StepF12 0.107663 0.0433 Inf 2.487 0.3480
StepF7 - StepF8 0.075726 0.0433 Inf 1.749 0.8451
StepF7 - StepF9 0.108873 0.0433 Inf 2.515 0.3303
StepF7 - StepF10 0.052071 0.0433 Inf 1.203 0.9889
StepF7 - StepF11 0.063621 0.0433 Inf 1.470 0.9488
StepF7 - StepF12 0.160476 0.0433 Inf 3.707 0.0113
StepF8 - StepF9 0.033147 0.0433 Inf 0.766 0.9998
StepF8 - StepF10 -0.023654 0.0433 Inf -0.546 1.0000
StepF8 - StepF11 -0.012105 0.0433 Inf -0.280 1.0000
StepF8 - StepF12 0.084750 0.0433 Inf 1.958 0.7222
StepF9 - StepF10 -0.056801 0.0433 Inf -1.312 0.9778
StepF9 - StepF11 -0.045252 0.0433 Inf -1.045 0.9966
StepF9 - StepF12 0.051603 0.0433 Inf 1.192 0.9897
StepF10 - StepF11 0.011550 0.0433 Inf 0.267 1.0000
StepF10 - StepF12 0.108404 0.0433 Inf 2.504 0.3371
StepF11 - StepF12 0.096855 0.0433 Inf 2.237 0.5221
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.257079 0.0433 Inf -5.939 <.0001
StepF1 - StepF3 -0.090156 0.0433 Inf -2.083 0.6354
StepF1 - StepF4 0.052115 0.0433 Inf 1.204 0.9888
StepF1 - StepF5 0.042898 0.0433 Inf 0.991 0.9979
StepF1 - StepF6 0.071171 0.0433 Inf 1.644 0.8928
StepF1 - StepF7 0.018358 0.0433 Inf 0.424 1.0000
StepF1 - StepF8 0.094084 0.0433 Inf 2.173 0.5692
StepF1 - StepF9 0.127231 0.0433 Inf 2.939 0.1273
StepF1 - StepF10 0.070430 0.0433 Inf 1.627 0.8995
StepF1 - StepF11 0.081979 0.0433 Inf 1.894 0.7635
StepF1 - StepF12 0.178834 0.0433 Inf 4.131 0.0021
StepF2 - StepF3 0.166923 0.0433 Inf 3.856 0.0065
StepF2 - StepF4 0.309194 0.0433 Inf 7.142 <.0001
StepF2 - StepF5 0.299977 0.0433 Inf 6.930 <.0001
StepF2 - StepF6 0.328250 0.0433 Inf 7.583 <.0001
StepF2 - StepF7 0.275437 0.0433 Inf 6.363 <.0001
StepF2 - StepF8 0.351163 0.0433 Inf 8.112 <.0001
StepF2 - StepF9 0.384310 0.0433 Inf 8.878 <.0001
StepF2 - StepF10 0.327509 0.0433 Inf 7.566 <.0001
StepF2 - StepF11 0.339058 0.0433 Inf 7.832 <.0001
StepF2 - StepF12 0.435913 0.0433 Inf 10.070 <.0001
StepF3 - StepF4 0.142271 0.0433 Inf 3.286 0.0472
StepF3 - StepF5 0.133054 0.0433 Inf 3.074 0.0886
StepF3 - StepF6 0.161327 0.0433 Inf 3.727 0.0105
StepF3 - StepF7 0.108514 0.0433 Inf 2.507 0.3355
StepF3 - StepF8 0.184240 0.0433 Inf 4.256 0.0013
StepF3 - StepF9 0.217387 0.0433 Inf 5.022 <.0001
StepF3 - StepF10 0.160586 0.0433 Inf 3.710 0.0112
StepF3 - StepF11 0.172135 0.0433 Inf 3.976 0.0040
StepF3 - StepF12 0.268990 0.0433 Inf 6.214 <.0001
StepF4 - StepF5 -0.009217 0.0433 Inf -0.213 1.0000
StepF4 - StepF6 0.019056 0.0433 Inf 0.440 1.0000
StepF4 - StepF7 -0.033757 0.0433 Inf -0.780 0.9998
StepF4 - StepF8 0.041969 0.0433 Inf 0.969 0.9983
StepF4 - StepF9 0.075116 0.0433 Inf 1.735 0.8521
StepF4 - StepF10 0.018315 0.0433 Inf 0.423 1.0000
StepF4 - StepF11 0.029864 0.0433 Inf 0.690 0.9999
StepF4 - StepF12 0.126719 0.0433 Inf 2.927 0.1312
StepF5 - StepF6 0.028273 0.0433 Inf 0.653 1.0000
StepF5 - StepF7 -0.024539 0.0433 Inf -0.567 1.0000
StepF5 - StepF8 0.051186 0.0433 Inf 1.182 0.9903
StepF5 - StepF9 0.084334 0.0433 Inf 1.948 0.7286
StepF5 - StepF10 0.027532 0.0433 Inf 0.636 1.0000
StepF5 - StepF11 0.039082 0.0433 Inf 0.903 0.9991
StepF5 - StepF12 0.135936 0.0433 Inf 3.140 0.0733
StepF6 - StepF7 -0.052813 0.0433 Inf -1.220 0.9875
StepF6 - StepF8 0.022913 0.0433 Inf 0.529 1.0000
StepF6 - StepF9 0.056060 0.0433 Inf 1.295 0.9799
StepF6 - StepF10 -0.000741 0.0433 Inf -0.017 1.0000
StepF6 - StepF11 0.010808 0.0433 Inf 0.250 1.0000
StepF6 - StepF12 0.107663 0.0433 Inf 2.487 0.3480
StepF7 - StepF8 0.075726 0.0433 Inf 1.749 0.8451
StepF7 - StepF9 0.108873 0.0433 Inf 2.515 0.3303
StepF7 - StepF10 0.052071 0.0433 Inf 1.203 0.9889
StepF7 - StepF11 0.063621 0.0433 Inf 1.470 0.9488
StepF7 - StepF12 0.160476 0.0433 Inf 3.707 0.0113
StepF8 - StepF9 0.033147 0.0433 Inf 0.766 0.9998
StepF8 - StepF10 -0.023654 0.0433 Inf -0.546 1.0000
StepF8 - StepF11 -0.012105 0.0433 Inf -0.280 1.0000
StepF8 - StepF12 0.084750 0.0433 Inf 1.958 0.7222
StepF9 - StepF10 -0.056801 0.0433 Inf -1.312 0.9778
StepF9 - StepF11 -0.045252 0.0433 Inf -1.045 0.9966
StepF9 - StepF12 0.051603 0.0433 Inf 1.192 0.9897
StepF10 - StepF11 0.011550 0.0433 Inf 0.267 1.0000
StepF10 - StepF12 0.108404 0.0433 Inf 2.504 0.3371
StepF11 - StepF12 0.096855 0.0433 Inf 2.237 0.5221
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 12 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.25708 0.0433 Inf 5.939 <.0001
StepF3 - StepF2 -0.16692 0.0433 Inf -3.856 0.0012
StepF4 - StepF3 -0.14227 0.0433 Inf -3.286 0.0091
StepF5 - StepF4 0.00922 0.0433 Inf 0.213 1.0000
StepF6 - StepF5 -0.02827 0.0433 Inf -0.653 1.0000
StepF7 - StepF6 0.05281 0.0433 Inf 1.220 1.0000
StepF8 - StepF7 -0.07573 0.0433 Inf -1.749 0.5617
StepF9 - StepF8 -0.03315 0.0433 Inf -0.766 1.0000
StepF10 - StepF9 0.05680 0.0433 Inf 1.312 1.0000
StepF11 - StepF10 -0.01155 0.0433 Inf -0.267 1.0000
StepF12 - StepF11 -0.09685 0.0433 Inf -2.237 0.2021
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.25708 0.0433 Inf 5.939 <.0001
StepF3 - StepF2 -0.16692 0.0433 Inf -3.856 0.0012
StepF4 - StepF3 -0.14227 0.0433 Inf -3.286 0.0091
StepF5 - StepF4 0.00922 0.0433 Inf 0.213 1.0000
StepF6 - StepF5 -0.02827 0.0433 Inf -0.653 1.0000
StepF7 - StepF6 0.05281 0.0433 Inf 1.220 1.0000
StepF8 - StepF7 -0.07573 0.0433 Inf -1.749 0.5617
StepF9 - StepF8 -0.03315 0.0433 Inf -0.766 1.0000
StepF10 - StepF9 0.05680 0.0433 Inf 1.312 1.0000
StepF11 - StepF10 -0.01155 0.0433 Inf -0.267 1.0000
StepF12 - StepF11 -0.09685 0.0433 Inf -2.237 0.2021
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 11 tests .report_step_test(sw_b5_18, "5", "18 steps")
==============================
TEST | Block 5 | 18 steps | Axis X
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 115.8727 17 <2e-16 ***
Accuracy 0.0706 1 0.7905
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.666 0.0513 Inf 0.565 0.766
2 0.602 0.0513 Inf 0.502 0.703
3 0.695 0.0513 Inf 0.594 0.796
4 0.602 0.0513 Inf 0.501 0.702
5 0.559 0.0513 Inf 0.458 0.660
6 0.571 0.0513 Inf 0.471 0.672
7 0.633 0.0513 Inf 0.532 0.733
8 0.566 0.0513 Inf 0.466 0.667
9 0.556 0.0513 Inf 0.456 0.657
10 0.610 0.0513 Inf 0.509 0.710
11 0.633 0.0513 Inf 0.532 0.734
12 0.527 0.0513 Inf 0.427 0.628
13 0.576 0.0513 Inf 0.475 0.676
14 0.601 0.0513 Inf 0.501 0.702
15 0.591 0.0513 Inf 0.490 0.691
16 0.547 0.0513 Inf 0.446 0.647
17 0.530 0.0513 Inf 0.429 0.630
18 0.527 0.0513 Inf 0.426 0.627
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.662 0.0515 Inf 0.561 0.763
2 0.599 0.0515 Inf 0.498 0.700
3 0.691 0.0515 Inf 0.591 0.792
4 0.598 0.0515 Inf 0.497 0.699
5 0.556 0.0515 Inf 0.455 0.656
6 0.568 0.0515 Inf 0.467 0.668
7 0.629 0.0515 Inf 0.528 0.730
8 0.563 0.0515 Inf 0.462 0.664
9 0.553 0.0515 Inf 0.452 0.654
10 0.606 0.0515 Inf 0.505 0.707
11 0.630 0.0515 Inf 0.529 0.730
12 0.524 0.0515 Inf 0.423 0.625
13 0.572 0.0515 Inf 0.472 0.673
14 0.598 0.0515 Inf 0.497 0.699
15 0.587 0.0515 Inf 0.486 0.688
16 0.543 0.0515 Inf 0.442 0.644
17 0.526 0.0515 Inf 0.425 0.627
18 0.523 0.0515 Inf 0.422 0.624
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.063268 0.0255 Inf 2.477 0.5481
StepF1 - StepF3 -0.029373 0.0255 Inf -1.150 0.9996
StepF1 - StepF4 0.063963 0.0255 Inf 2.504 0.5269
StepF1 - StepF5 0.106536 0.0255 Inf 4.171 0.0040
StepF1 - StepF6 0.094481 0.0255 Inf 3.699 0.0245
StepF1 - StepF7 0.033013 0.0255 Inf 1.293 0.9984
StepF1 - StepF8 0.099413 0.0255 Inf 3.892 0.0121
StepF1 - StepF9 0.109111 0.0255 Inf 4.272 0.0026
StepF1 - StepF10 0.056026 0.0255 Inf 2.193 0.7584
StepF1 - StepF11 0.032532 0.0255 Inf 1.274 0.9986
StepF1 - StepF12 0.138166 0.0255 Inf 5.409 <.0001
StepF1 - StepF13 0.089730 0.0255 Inf 3.513 0.0462
StepF1 - StepF14 0.064347 0.0255 Inf 2.519 0.5153
StepF1 - StepF15 0.074933 0.0255 Inf 2.934 0.2337
StepF1 - StepF16 0.118893 0.0255 Inf 4.655 0.0005
StepF1 - StepF17 0.136041 0.0255 Inf 5.326 <.0001
StepF1 - StepF18 0.138829 0.0255 Inf 5.435 <.0001
StepF2 - StepF3 -0.092641 0.0255 Inf -3.627 0.0315
StepF2 - StepF4 0.000695 0.0255 Inf 0.027 1.0000
StepF2 - StepF5 0.043268 0.0255 Inf 1.694 0.9681
StepF2 - StepF6 0.031213 0.0255 Inf 1.222 0.9992
StepF2 - StepF7 -0.030255 0.0255 Inf -1.185 0.9995
StepF2 - StepF8 0.036145 0.0255 Inf 1.415 0.9952
StepF2 - StepF9 0.045843 0.0255 Inf 1.795 0.9458
StepF2 - StepF10 -0.007242 0.0255 Inf -0.284 1.0000
StepF2 - StepF11 -0.030735 0.0255 Inf -1.203 0.9993
StepF2 - StepF12 0.074898 0.0255 Inf 2.932 0.2344
StepF2 - StepF13 0.026462 0.0255 Inf 1.036 0.9999
StepF2 - StepF14 0.001079 0.0255 Inf 0.042 1.0000
StepF2 - StepF15 0.011665 0.0255 Inf 0.457 1.0000
StepF2 - StepF16 0.055625 0.0255 Inf 2.178 0.7687
StepF2 - StepF17 0.072773 0.0255 Inf 2.849 0.2820
StepF2 - StepF18 0.075561 0.0255 Inf 2.958 0.2207
StepF3 - StepF4 0.093336 0.0255 Inf 3.654 0.0287
StepF3 - StepF5 0.135909 0.0255 Inf 5.321 <.0001
StepF3 - StepF6 0.123854 0.0255 Inf 4.849 0.0002
StepF3 - StepF7 0.062386 0.0255 Inf 2.443 0.5750
StepF3 - StepF8 0.128786 0.0255 Inf 5.042 0.0001
StepF3 - StepF9 0.138484 0.0255 Inf 5.422 <.0001
StepF3 - StepF10 0.085399 0.0255 Inf 3.343 0.0786
StepF3 - StepF11 0.061906 0.0255 Inf 2.424 0.5896
StepF3 - StepF12 0.167539 0.0255 Inf 6.559 <.0001
StepF3 - StepF13 0.119103 0.0255 Inf 4.663 0.0004
StepF3 - StepF14 0.093720 0.0255 Inf 3.669 0.0272
StepF3 - StepF15 0.104306 0.0255 Inf 4.084 0.0057
StepF3 - StepF16 0.148266 0.0255 Inf 5.805 <.0001
StepF3 - StepF17 0.165414 0.0255 Inf 6.476 <.0001
StepF3 - StepF18 0.168202 0.0255 Inf 6.585 <.0001
StepF4 - StepF5 0.042573 0.0255 Inf 1.667 0.9727
StepF4 - StepF6 0.030517 0.0255 Inf 1.195 0.9994
StepF4 - StepF7 -0.030950 0.0255 Inf -1.212 0.9993
StepF4 - StepF8 0.035450 0.0255 Inf 1.388 0.9962
StepF4 - StepF9 0.045147 0.0255 Inf 1.768 0.9527
StepF4 - StepF10 -0.007938 0.0255 Inf -0.311 1.0000
StepF4 - StepF11 -0.031431 0.0255 Inf -1.231 0.9991
StepF4 - StepF12 0.074203 0.0255 Inf 2.905 0.2494
StepF4 - StepF13 0.025767 0.0255 Inf 1.009 0.9999
StepF4 - StepF14 0.000383 0.0255 Inf 0.015 1.0000
StepF4 - StepF15 0.010970 0.0255 Inf 0.429 1.0000
StepF4 - StepF16 0.054930 0.0255 Inf 2.151 0.7861
StepF4 - StepF17 0.072078 0.0255 Inf 2.822 0.2987
StepF4 - StepF18 0.074866 0.0255 Inf 2.931 0.2351
StepF5 - StepF6 -0.012056 0.0255 Inf -0.472 1.0000
StepF5 - StepF7 -0.073523 0.0255 Inf -2.879 0.2646
StepF5 - StepF8 -0.007123 0.0255 Inf -0.279 1.0000
StepF5 - StepF9 0.002574 0.0255 Inf 0.101 1.0000
StepF5 - StepF10 -0.050511 0.0255 Inf -1.978 0.8803
StepF5 - StepF11 -0.074004 0.0255 Inf -2.897 0.2538
StepF5 - StepF12 0.031630 0.0255 Inf 1.238 0.9990
StepF5 - StepF13 -0.016806 0.0255 Inf -0.658 1.0000
StepF5 - StepF14 -0.042189 0.0255 Inf -1.652 0.9750
StepF5 - StepF15 -0.031603 0.0255 Inf -1.237 0.9991
StepF5 - StepF16 0.012357 0.0255 Inf 0.484 1.0000
StepF5 - StepF17 0.029505 0.0255 Inf 1.155 0.9996
StepF5 - StepF18 0.032293 0.0255 Inf 1.264 0.9988
StepF6 - StepF7 -0.061468 0.0255 Inf -2.407 0.6029
StepF6 - StepF8 0.004932 0.0255 Inf 0.193 1.0000
StepF6 - StepF9 0.014630 0.0255 Inf 0.573 1.0000
StepF6 - StepF10 -0.038455 0.0255 Inf -1.506 0.9904
StepF6 - StepF11 -0.061948 0.0255 Inf -2.425 0.5883
StepF6 - StepF12 0.043685 0.0255 Inf 1.710 0.9650
StepF6 - StepF13 -0.004751 0.0255 Inf -0.186 1.0000
StepF6 - StepF14 -0.030134 0.0255 Inf -1.180 0.9995
StepF6 - StepF15 -0.019548 0.0255 Inf -0.765 1.0000
StepF6 - StepF16 0.024412 0.0255 Inf 0.956 1.0000
StepF6 - StepF17 0.041560 0.0255 Inf 1.627 0.9785
StepF6 - StepF18 0.044348 0.0255 Inf 1.736 0.9598
StepF7 - StepF8 0.066400 0.0255 Inf 2.600 0.4537
StepF7 - StepF9 0.076098 0.0255 Inf 2.979 0.2100
StepF7 - StepF10 0.023013 0.0255 Inf 0.901 1.0000
StepF7 - StepF11 -0.000480 0.0255 Inf -0.019 1.0000
StepF7 - StepF12 0.105153 0.0255 Inf 4.117 0.0050
StepF7 - StepF13 0.056717 0.0255 Inf 2.221 0.7401
StepF7 - StepF14 0.031334 0.0255 Inf 1.227 0.9991
StepF7 - StepF15 0.041920 0.0255 Inf 1.641 0.9765
StepF7 - StepF16 0.085880 0.0255 Inf 3.362 0.0743
StepF7 - StepF17 0.103028 0.0255 Inf 4.034 0.0070
StepF7 - StepF18 0.105816 0.0255 Inf 4.143 0.0045
StepF8 - StepF9 0.009698 0.0255 Inf 0.380 1.0000
StepF8 - StepF10 -0.043387 0.0255 Inf -1.699 0.9672
StepF8 - StepF11 -0.066880 0.0255 Inf -2.618 0.4395
StepF8 - StepF12 0.038753 0.0255 Inf 1.517 0.9896
StepF8 - StepF13 -0.009683 0.0255 Inf -0.379 1.0000
StepF8 - StepF14 -0.035066 0.0255 Inf -1.373 0.9966
StepF8 - StepF15 -0.024480 0.0255 Inf -0.958 1.0000
StepF8 - StepF16 0.019480 0.0255 Inf 0.763 1.0000
StepF8 - StepF17 0.036628 0.0255 Inf 1.434 0.9944
StepF8 - StepF18 0.039416 0.0255 Inf 1.543 0.9875
StepF9 - StepF10 -0.053085 0.0255 Inf -2.078 0.8291
StepF9 - StepF11 -0.076578 0.0255 Inf -2.998 0.2007
StepF9 - StepF12 0.029055 0.0255 Inf 1.138 0.9997
StepF9 - StepF13 -0.019381 0.0255 Inf -0.759 1.0000
StepF9 - StepF14 -0.044764 0.0255 Inf -1.753 0.9562
StepF9 - StepF15 -0.034178 0.0255 Inf -1.338 0.9975
StepF9 - StepF16 0.009782 0.0255 Inf 0.383 1.0000
StepF9 - StepF17 0.026930 0.0255 Inf 1.054 0.9999
StepF9 - StepF18 0.029718 0.0255 Inf 1.164 0.9996
StepF10 - StepF11 -0.023493 0.0255 Inf -0.920 1.0000
StepF10 - StepF12 0.082140 0.0255 Inf 3.216 0.1138
StepF10 - StepF13 0.033704 0.0255 Inf 1.320 0.9979
StepF10 - StepF14 0.008321 0.0255 Inf 0.326 1.0000
StepF10 - StepF15 0.018907 0.0255 Inf 0.740 1.0000
StepF10 - StepF16 0.062867 0.0255 Inf 2.461 0.5603
StepF10 - StepF17 0.080015 0.0255 Inf 3.133 0.1427
StepF10 - StepF18 0.082803 0.0255 Inf 3.242 0.1057
StepF11 - StepF12 0.105633 0.0255 Inf 4.136 0.0046
StepF11 - StepF13 0.057197 0.0255 Inf 2.239 0.7271
StepF11 - StepF14 0.031814 0.0255 Inf 1.246 0.9990
StepF11 - StepF15 0.042401 0.0255 Inf 1.660 0.9737
StepF11 - StepF16 0.086360 0.0255 Inf 3.381 0.0701
StepF11 - StepF17 0.103508 0.0255 Inf 4.052 0.0065
StepF11 - StepF18 0.106296 0.0255 Inf 4.162 0.0041
StepF12 - StepF13 -0.048436 0.0255 Inf -1.896 0.9137
StepF12 - StepF14 -0.073819 0.0255 Inf -2.890 0.2579
StepF12 - StepF15 -0.063233 0.0255 Inf -2.476 0.5492
StepF12 - StepF16 -0.019273 0.0255 Inf -0.755 1.0000
StepF12 - StepF17 -0.002125 0.0255 Inf -0.083 1.0000
StepF12 - StepF18 0.000663 0.0255 Inf 0.026 1.0000
StepF13 - StepF14 -0.025383 0.0255 Inf -0.994 0.9999
StepF13 - StepF15 -0.014797 0.0255 Inf -0.579 1.0000
StepF13 - StepF16 0.029163 0.0255 Inf 1.142 0.9997
StepF13 - StepF17 0.046311 0.0255 Inf 1.813 0.9407
StepF13 - StepF18 0.049099 0.0255 Inf 1.922 0.9038
StepF14 - StepF15 0.010586 0.0255 Inf 0.414 1.0000
StepF14 - StepF16 0.054546 0.0255 Inf 2.136 0.7955
StepF14 - StepF17 0.071694 0.0255 Inf 2.807 0.3082
StepF14 - StepF18 0.074482 0.0255 Inf 2.916 0.2433
StepF15 - StepF16 0.043960 0.0255 Inf 1.721 0.9629
StepF15 - StepF17 0.061108 0.0255 Inf 2.392 0.6138
StepF15 - StepF18 0.063896 0.0255 Inf 2.502 0.5290
StepF16 - StepF17 0.017148 0.0255 Inf 0.671 1.0000
StepF16 - StepF18 0.019936 0.0255 Inf 0.781 1.0000
StepF17 - StepF18 0.002788 0.0255 Inf 0.109 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 0.063268 0.0255 Inf 2.477 0.5481
StepF1 - StepF3 -0.029373 0.0255 Inf -1.150 0.9996
StepF1 - StepF4 0.063963 0.0255 Inf 2.504 0.5269
StepF1 - StepF5 0.106536 0.0255 Inf 4.171 0.0040
StepF1 - StepF6 0.094481 0.0255 Inf 3.699 0.0245
StepF1 - StepF7 0.033013 0.0255 Inf 1.293 0.9984
StepF1 - StepF8 0.099413 0.0255 Inf 3.892 0.0121
StepF1 - StepF9 0.109111 0.0255 Inf 4.272 0.0026
StepF1 - StepF10 0.056026 0.0255 Inf 2.193 0.7584
StepF1 - StepF11 0.032532 0.0255 Inf 1.274 0.9986
StepF1 - StepF12 0.138166 0.0255 Inf 5.409 <.0001
StepF1 - StepF13 0.089730 0.0255 Inf 3.513 0.0462
StepF1 - StepF14 0.064347 0.0255 Inf 2.519 0.5153
StepF1 - StepF15 0.074933 0.0255 Inf 2.934 0.2337
StepF1 - StepF16 0.118893 0.0255 Inf 4.655 0.0005
StepF1 - StepF17 0.136041 0.0255 Inf 5.326 <.0001
StepF1 - StepF18 0.138829 0.0255 Inf 5.435 <.0001
StepF2 - StepF3 -0.092641 0.0255 Inf -3.627 0.0315
StepF2 - StepF4 0.000695 0.0255 Inf 0.027 1.0000
StepF2 - StepF5 0.043268 0.0255 Inf 1.694 0.9681
StepF2 - StepF6 0.031213 0.0255 Inf 1.222 0.9992
StepF2 - StepF7 -0.030255 0.0255 Inf -1.185 0.9995
StepF2 - StepF8 0.036145 0.0255 Inf 1.415 0.9952
StepF2 - StepF9 0.045843 0.0255 Inf 1.795 0.9458
StepF2 - StepF10 -0.007242 0.0255 Inf -0.284 1.0000
StepF2 - StepF11 -0.030735 0.0255 Inf -1.203 0.9993
StepF2 - StepF12 0.074898 0.0255 Inf 2.932 0.2344
StepF2 - StepF13 0.026462 0.0255 Inf 1.036 0.9999
StepF2 - StepF14 0.001079 0.0255 Inf 0.042 1.0000
StepF2 - StepF15 0.011665 0.0255 Inf 0.457 1.0000
StepF2 - StepF16 0.055625 0.0255 Inf 2.178 0.7687
StepF2 - StepF17 0.072773 0.0255 Inf 2.849 0.2820
StepF2 - StepF18 0.075561 0.0255 Inf 2.958 0.2207
StepF3 - StepF4 0.093336 0.0255 Inf 3.654 0.0287
StepF3 - StepF5 0.135909 0.0255 Inf 5.321 <.0001
StepF3 - StepF6 0.123854 0.0255 Inf 4.849 0.0002
StepF3 - StepF7 0.062386 0.0255 Inf 2.443 0.5750
StepF3 - StepF8 0.128786 0.0255 Inf 5.042 0.0001
StepF3 - StepF9 0.138484 0.0255 Inf 5.422 <.0001
StepF3 - StepF10 0.085399 0.0255 Inf 3.343 0.0786
StepF3 - StepF11 0.061906 0.0255 Inf 2.424 0.5896
StepF3 - StepF12 0.167539 0.0255 Inf 6.559 <.0001
StepF3 - StepF13 0.119103 0.0255 Inf 4.663 0.0004
StepF3 - StepF14 0.093720 0.0255 Inf 3.669 0.0272
StepF3 - StepF15 0.104306 0.0255 Inf 4.084 0.0057
StepF3 - StepF16 0.148266 0.0255 Inf 5.805 <.0001
StepF3 - StepF17 0.165414 0.0255 Inf 6.476 <.0001
StepF3 - StepF18 0.168202 0.0255 Inf 6.585 <.0001
StepF4 - StepF5 0.042573 0.0255 Inf 1.667 0.9727
StepF4 - StepF6 0.030517 0.0255 Inf 1.195 0.9994
StepF4 - StepF7 -0.030950 0.0255 Inf -1.212 0.9993
StepF4 - StepF8 0.035450 0.0255 Inf 1.388 0.9962
StepF4 - StepF9 0.045147 0.0255 Inf 1.768 0.9527
StepF4 - StepF10 -0.007938 0.0255 Inf -0.311 1.0000
StepF4 - StepF11 -0.031431 0.0255 Inf -1.231 0.9991
StepF4 - StepF12 0.074203 0.0255 Inf 2.905 0.2494
StepF4 - StepF13 0.025767 0.0255 Inf 1.009 0.9999
StepF4 - StepF14 0.000383 0.0255 Inf 0.015 1.0000
StepF4 - StepF15 0.010970 0.0255 Inf 0.429 1.0000
StepF4 - StepF16 0.054930 0.0255 Inf 2.151 0.7861
StepF4 - StepF17 0.072078 0.0255 Inf 2.822 0.2987
StepF4 - StepF18 0.074866 0.0255 Inf 2.931 0.2351
StepF5 - StepF6 -0.012056 0.0255 Inf -0.472 1.0000
StepF5 - StepF7 -0.073523 0.0255 Inf -2.879 0.2646
StepF5 - StepF8 -0.007123 0.0255 Inf -0.279 1.0000
StepF5 - StepF9 0.002574 0.0255 Inf 0.101 1.0000
StepF5 - StepF10 -0.050511 0.0255 Inf -1.978 0.8803
StepF5 - StepF11 -0.074004 0.0255 Inf -2.897 0.2538
StepF5 - StepF12 0.031630 0.0255 Inf 1.238 0.9990
StepF5 - StepF13 -0.016806 0.0255 Inf -0.658 1.0000
StepF5 - StepF14 -0.042189 0.0255 Inf -1.652 0.9750
StepF5 - StepF15 -0.031603 0.0255 Inf -1.237 0.9991
StepF5 - StepF16 0.012357 0.0255 Inf 0.484 1.0000
StepF5 - StepF17 0.029505 0.0255 Inf 1.155 0.9996
StepF5 - StepF18 0.032293 0.0255 Inf 1.264 0.9988
StepF6 - StepF7 -0.061468 0.0255 Inf -2.407 0.6029
StepF6 - StepF8 0.004932 0.0255 Inf 0.193 1.0000
StepF6 - StepF9 0.014630 0.0255 Inf 0.573 1.0000
StepF6 - StepF10 -0.038455 0.0255 Inf -1.506 0.9904
StepF6 - StepF11 -0.061948 0.0255 Inf -2.425 0.5883
StepF6 - StepF12 0.043685 0.0255 Inf 1.710 0.9650
StepF6 - StepF13 -0.004751 0.0255 Inf -0.186 1.0000
StepF6 - StepF14 -0.030134 0.0255 Inf -1.180 0.9995
StepF6 - StepF15 -0.019548 0.0255 Inf -0.765 1.0000
StepF6 - StepF16 0.024412 0.0255 Inf 0.956 1.0000
StepF6 - StepF17 0.041560 0.0255 Inf 1.627 0.9785
StepF6 - StepF18 0.044348 0.0255 Inf 1.736 0.9598
StepF7 - StepF8 0.066400 0.0255 Inf 2.600 0.4537
StepF7 - StepF9 0.076098 0.0255 Inf 2.979 0.2100
StepF7 - StepF10 0.023013 0.0255 Inf 0.901 1.0000
StepF7 - StepF11 -0.000480 0.0255 Inf -0.019 1.0000
StepF7 - StepF12 0.105153 0.0255 Inf 4.117 0.0050
StepF7 - StepF13 0.056717 0.0255 Inf 2.221 0.7401
StepF7 - StepF14 0.031334 0.0255 Inf 1.227 0.9991
StepF7 - StepF15 0.041920 0.0255 Inf 1.641 0.9765
StepF7 - StepF16 0.085880 0.0255 Inf 3.362 0.0743
StepF7 - StepF17 0.103028 0.0255 Inf 4.034 0.0070
StepF7 - StepF18 0.105816 0.0255 Inf 4.143 0.0045
StepF8 - StepF9 0.009698 0.0255 Inf 0.380 1.0000
StepF8 - StepF10 -0.043387 0.0255 Inf -1.699 0.9672
StepF8 - StepF11 -0.066880 0.0255 Inf -2.618 0.4395
StepF8 - StepF12 0.038753 0.0255 Inf 1.517 0.9896
StepF8 - StepF13 -0.009683 0.0255 Inf -0.379 1.0000
StepF8 - StepF14 -0.035066 0.0255 Inf -1.373 0.9966
StepF8 - StepF15 -0.024480 0.0255 Inf -0.958 1.0000
StepF8 - StepF16 0.019480 0.0255 Inf 0.763 1.0000
StepF8 - StepF17 0.036628 0.0255 Inf 1.434 0.9944
StepF8 - StepF18 0.039416 0.0255 Inf 1.543 0.9875
StepF9 - StepF10 -0.053085 0.0255 Inf -2.078 0.8291
StepF9 - StepF11 -0.076578 0.0255 Inf -2.998 0.2007
StepF9 - StepF12 0.029055 0.0255 Inf 1.138 0.9997
StepF9 - StepF13 -0.019381 0.0255 Inf -0.759 1.0000
StepF9 - StepF14 -0.044764 0.0255 Inf -1.753 0.9562
StepF9 - StepF15 -0.034178 0.0255 Inf -1.338 0.9975
StepF9 - StepF16 0.009782 0.0255 Inf 0.383 1.0000
StepF9 - StepF17 0.026930 0.0255 Inf 1.054 0.9999
StepF9 - StepF18 0.029718 0.0255 Inf 1.164 0.9996
StepF10 - StepF11 -0.023493 0.0255 Inf -0.920 1.0000
StepF10 - StepF12 0.082140 0.0255 Inf 3.216 0.1138
StepF10 - StepF13 0.033704 0.0255 Inf 1.320 0.9979
StepF10 - StepF14 0.008321 0.0255 Inf 0.326 1.0000
StepF10 - StepF15 0.018907 0.0255 Inf 0.740 1.0000
StepF10 - StepF16 0.062867 0.0255 Inf 2.461 0.5603
StepF10 - StepF17 0.080015 0.0255 Inf 3.133 0.1427
StepF10 - StepF18 0.082803 0.0255 Inf 3.242 0.1057
StepF11 - StepF12 0.105633 0.0255 Inf 4.136 0.0046
StepF11 - StepF13 0.057197 0.0255 Inf 2.239 0.7271
StepF11 - StepF14 0.031814 0.0255 Inf 1.246 0.9990
StepF11 - StepF15 0.042401 0.0255 Inf 1.660 0.9737
StepF11 - StepF16 0.086360 0.0255 Inf 3.381 0.0701
StepF11 - StepF17 0.103508 0.0255 Inf 4.052 0.0065
StepF11 - StepF18 0.106296 0.0255 Inf 4.162 0.0041
StepF12 - StepF13 -0.048436 0.0255 Inf -1.896 0.9137
StepF12 - StepF14 -0.073819 0.0255 Inf -2.890 0.2579
StepF12 - StepF15 -0.063233 0.0255 Inf -2.476 0.5492
StepF12 - StepF16 -0.019273 0.0255 Inf -0.755 1.0000
StepF12 - StepF17 -0.002125 0.0255 Inf -0.083 1.0000
StepF12 - StepF18 0.000663 0.0255 Inf 0.026 1.0000
StepF13 - StepF14 -0.025383 0.0255 Inf -0.994 0.9999
StepF13 - StepF15 -0.014797 0.0255 Inf -0.579 1.0000
StepF13 - StepF16 0.029163 0.0255 Inf 1.142 0.9997
StepF13 - StepF17 0.046311 0.0255 Inf 1.813 0.9407
StepF13 - StepF18 0.049099 0.0255 Inf 1.922 0.9038
StepF14 - StepF15 0.010586 0.0255 Inf 0.414 1.0000
StepF14 - StepF16 0.054546 0.0255 Inf 2.136 0.7955
StepF14 - StepF17 0.071694 0.0255 Inf 2.807 0.3082
StepF14 - StepF18 0.074482 0.0255 Inf 2.916 0.2433
StepF15 - StepF16 0.043960 0.0255 Inf 1.721 0.9629
StepF15 - StepF17 0.061108 0.0255 Inf 2.392 0.6138
StepF15 - StepF18 0.063896 0.0255 Inf 2.502 0.5290
StepF16 - StepF17 0.017148 0.0255 Inf 0.671 1.0000
StepF16 - StepF18 0.019936 0.0255 Inf 0.781 1.0000
StepF17 - StepF18 0.002788 0.0255 Inf 0.109 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.06327 0.0255 Inf -2.477 0.1722
StepF3 - StepF2 0.09264 0.0255 Inf 3.627 0.0043
StepF4 - StepF3 -0.09334 0.0255 Inf -3.654 0.0041
StepF5 - StepF4 -0.04257 0.0255 Inf -1.667 0.7671
StepF6 - StepF5 0.01206 0.0255 Inf 0.472 1.0000
StepF7 - StepF6 0.06147 0.0255 Inf 2.407 0.1932
StepF8 - StepF7 -0.06640 0.0255 Inf -2.600 0.1306
StepF9 - StepF8 -0.00970 0.0255 Inf -0.380 1.0000
StepF10 - StepF9 0.05309 0.0255 Inf 2.078 0.4144
StepF11 - StepF10 0.02349 0.0255 Inf 0.920 1.0000
StepF12 - StepF11 -0.10563 0.0255 Inf -4.136 0.0006
StepF13 - StepF12 0.04844 0.0255 Inf 1.896 0.5792
StepF14 - StepF13 0.02538 0.0255 Inf 0.994 1.0000
StepF15 - StepF14 -0.01059 0.0255 Inf -0.414 1.0000
StepF16 - StepF15 -0.04396 0.0255 Inf -1.721 0.7671
StepF17 - StepF16 -0.01715 0.0255 Inf -0.671 1.0000
StepF18 - StepF17 -0.00279 0.0255 Inf -0.109 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 -0.06327 0.0255 Inf -2.477 0.1722
StepF3 - StepF2 0.09264 0.0255 Inf 3.627 0.0043
StepF4 - StepF3 -0.09334 0.0255 Inf -3.654 0.0041
StepF5 - StepF4 -0.04257 0.0255 Inf -1.667 0.7671
StepF6 - StepF5 0.01206 0.0255 Inf 0.472 1.0000
StepF7 - StepF6 0.06147 0.0255 Inf 2.407 0.1932
StepF8 - StepF7 -0.06640 0.0255 Inf -2.600 0.1306
StepF9 - StepF8 -0.00970 0.0255 Inf -0.380 1.0000
StepF10 - StepF9 0.05309 0.0255 Inf 2.078 0.4144
StepF11 - StepF10 0.02349 0.0255 Inf 0.920 1.0000
StepF12 - StepF11 -0.10563 0.0255 Inf -4.136 0.0006
StepF13 - StepF12 0.04844 0.0255 Inf 1.896 0.5792
StepF14 - StepF13 0.02538 0.0255 Inf 0.994 1.0000
StepF15 - StepF14 -0.01059 0.0255 Inf -0.414 1.0000
StepF16 - StepF15 -0.04396 0.0255 Inf -1.721 0.7671
StepF17 - StepF16 -0.01715 0.0255 Inf -0.671 1.0000
StepF18 - StepF17 -0.00279 0.0255 Inf -0.109 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests
==============================
TEST | Block 5 | 18 steps | Axis Y
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 82.4532 17 1.402e-10 ***
Accuracy 0.0996 1 0.7523
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.617 0.0719 Inf 0.476 0.758
2 0.807 0.0719 Inf 0.666 0.948
3 0.748 0.0719 Inf 0.607 0.889
4 0.643 0.0719 Inf 0.502 0.784
5 0.556 0.0719 Inf 0.415 0.697
6 0.604 0.0719 Inf 0.463 0.745
7 0.620 0.0719 Inf 0.479 0.761
8 0.687 0.0719 Inf 0.546 0.828
9 0.742 0.0719 Inf 0.601 0.883
10 0.744 0.0719 Inf 0.603 0.885
11 0.693 0.0719 Inf 0.552 0.834
12 0.581 0.0719 Inf 0.440 0.722
13 0.534 0.0719 Inf 0.393 0.675
14 0.606 0.0719 Inf 0.465 0.747
15 0.637 0.0719 Inf 0.496 0.778
16 0.597 0.0719 Inf 0.456 0.738
17 0.542 0.0719 Inf 0.401 0.683
18 0.532 0.0719 Inf 0.391 0.673
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 0.608 0.0724 Inf 0.467 0.750
2 0.799 0.0724 Inf 0.657 0.941
3 0.740 0.0724 Inf 0.598 0.882
4 0.635 0.0724 Inf 0.493 0.776
5 0.548 0.0724 Inf 0.406 0.689
6 0.595 0.0724 Inf 0.453 0.737
7 0.611 0.0724 Inf 0.469 0.753
8 0.678 0.0724 Inf 0.536 0.820
9 0.733 0.0724 Inf 0.591 0.875
10 0.736 0.0724 Inf 0.594 0.878
11 0.684 0.0724 Inf 0.543 0.826
12 0.573 0.0724 Inf 0.431 0.715
13 0.525 0.0724 Inf 0.383 0.667
14 0.597 0.0724 Inf 0.456 0.739
15 0.629 0.0724 Inf 0.487 0.770
16 0.589 0.0724 Inf 0.447 0.731
17 0.533 0.0724 Inf 0.391 0.675
18 0.524 0.0724 Inf 0.382 0.666
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.19042 0.0526 Inf -3.618 0.0325
StepF1 - StepF3 -0.13133 0.0526 Inf -2.495 0.5337
StepF1 - StepF4 -0.02627 0.0526 Inf -0.499 1.0000
StepF1 - StepF5 0.06084 0.0526 Inf 1.156 0.9996
StepF1 - StepF6 0.01336 0.0526 Inf 0.254 1.0000
StepF1 - StepF7 -0.00263 0.0526 Inf -0.050 1.0000
StepF1 - StepF8 -0.06959 0.0526 Inf -1.322 0.9978
StepF1 - StepF9 -0.12483 0.0526 Inf -2.372 0.6295
StepF1 - StepF10 -0.12729 0.0526 Inf -2.419 0.5935
StepF1 - StepF11 -0.07609 0.0526 Inf -1.446 0.9939
StepF1 - StepF12 0.03560 0.0526 Inf 0.676 1.0000
StepF1 - StepF13 0.08335 0.0526 Inf 1.584 0.9836
StepF1 - StepF14 0.01104 0.0526 Inf 0.210 1.0000
StepF1 - StepF15 -0.02016 0.0526 Inf -0.383 1.0000
StepF1 - StepF16 0.01964 0.0526 Inf 0.373 1.0000
StepF1 - StepF17 0.07513 0.0526 Inf 1.428 0.9947
StepF1 - StepF18 0.08457 0.0526 Inf 1.607 0.9810
StepF2 - StepF3 0.05908 0.0526 Inf 1.123 0.9997
StepF2 - StepF4 0.16415 0.0526 Inf 3.119 0.1479
StepF2 - StepF5 0.25126 0.0526 Inf 4.774 0.0003
StepF2 - StepF6 0.20378 0.0526 Inf 3.872 0.0130
StepF2 - StepF7 0.18779 0.0526 Inf 3.568 0.0385
StepF2 - StepF8 0.12083 0.0526 Inf 2.296 0.6865
StepF2 - StepF9 0.06559 0.0526 Inf 1.246 0.9990
StepF2 - StepF10 0.06313 0.0526 Inf 1.199 0.9994
StepF2 - StepF11 0.11433 0.0526 Inf 2.172 0.7723
StepF2 - StepF12 0.22601 0.0526 Inf 4.294 0.0024
StepF2 - StepF13 0.27377 0.0526 Inf 5.202 <.0001
StepF2 - StepF14 0.20146 0.0526 Inf 3.828 0.0154
StepF2 - StepF15 0.17026 0.0526 Inf 3.235 0.1078
StepF2 - StepF16 0.21006 0.0526 Inf 3.991 0.0082
StepF2 - StepF17 0.26555 0.0526 Inf 5.046 0.0001
StepF2 - StepF18 0.27499 0.0526 Inf 5.225 <.0001
StepF3 - StepF4 0.10507 0.0526 Inf 1.996 0.8715
StepF3 - StepF5 0.19217 0.0526 Inf 3.651 0.0290
StepF3 - StepF6 0.14470 0.0526 Inf 2.749 0.3460
StepF3 - StepF7 0.12870 0.0526 Inf 2.445 0.5727
StepF3 - StepF8 0.06175 0.0526 Inf 1.173 0.9995
StepF3 - StepF9 0.00650 0.0526 Inf 0.124 1.0000
StepF3 - StepF10 0.00404 0.0526 Inf 0.077 1.0000
StepF3 - StepF11 0.05524 0.0526 Inf 1.050 0.9999
StepF3 - StepF12 0.16693 0.0526 Inf 3.172 0.1285
StepF3 - StepF13 0.21468 0.0526 Inf 4.079 0.0058
StepF3 - StepF14 0.14237 0.0526 Inf 2.705 0.3765
StepF3 - StepF15 0.11117 0.0526 Inf 2.112 0.8094
StepF3 - StepF16 0.15098 0.0526 Inf 2.869 0.2703
StepF3 - StepF17 0.20647 0.0526 Inf 3.923 0.0107
StepF3 - StepF18 0.21590 0.0526 Inf 4.102 0.0053
StepF4 - StepF5 0.08710 0.0526 Inf 1.655 0.9745
StepF4 - StepF6 0.03963 0.0526 Inf 0.753 1.0000
StepF4 - StepF7 0.02363 0.0526 Inf 0.449 1.0000
StepF4 - StepF8 -0.04332 0.0526 Inf -0.823 1.0000
StepF4 - StepF9 -0.09856 0.0526 Inf -1.873 0.9221
StepF4 - StepF10 -0.10103 0.0526 Inf -1.920 0.9049
StepF4 - StepF11 -0.04983 0.0526 Inf -0.947 1.0000
StepF4 - StepF12 0.06186 0.0526 Inf 1.175 0.9995
StepF4 - StepF13 0.10961 0.0526 Inf 2.083 0.8266
StepF4 - StepF14 0.03730 0.0526 Inf 0.709 1.0000
StepF4 - StepF15 0.00611 0.0526 Inf 0.116 1.0000
StepF4 - StepF16 0.04591 0.0526 Inf 0.872 1.0000
StepF4 - StepF17 0.10140 0.0526 Inf 1.927 0.9020
StepF4 - StepF18 0.11083 0.0526 Inf 2.106 0.8133
StepF5 - StepF6 -0.04748 0.0526 Inf -0.902 1.0000
StepF5 - StepF7 -0.06347 0.0526 Inf -1.206 0.9993
StepF5 - StepF8 -0.13042 0.0526 Inf -2.478 0.5472
StepF5 - StepF9 -0.18567 0.0526 Inf -3.528 0.0440
StepF5 - StepF10 -0.18813 0.0526 Inf -3.575 0.0377
StepF5 - StepF11 -0.13693 0.0526 Inf -2.602 0.4520
StepF5 - StepF12 -0.02524 0.0526 Inf -0.480 1.0000
StepF5 - StepF13 0.02251 0.0526 Inf 0.428 1.0000
StepF5 - StepF14 -0.04980 0.0526 Inf -0.946 1.0000
StepF5 - StepF15 -0.08100 0.0526 Inf -1.539 0.9879
StepF5 - StepF16 -0.04120 0.0526 Inf -0.783 1.0000
StepF5 - StepF17 0.01429 0.0526 Inf 0.272 1.0000
StepF5 - StepF18 0.02373 0.0526 Inf 0.451 1.0000
StepF6 - StepF7 -0.01599 0.0526 Inf -0.304 1.0000
StepF6 - StepF8 -0.08295 0.0526 Inf -1.576 0.9844
StepF6 - StepF9 -0.13819 0.0526 Inf -2.626 0.4341
StepF6 - StepF10 -0.14065 0.0526 Inf -2.673 0.3998
StepF6 - StepF11 -0.08945 0.0526 Inf -1.700 0.9670
StepF6 - StepF12 0.02223 0.0526 Inf 0.422 1.0000
StepF6 - StepF13 0.06999 0.0526 Inf 1.330 0.9977
StepF6 - StepF14 -0.00232 0.0526 Inf -0.044 1.0000
StepF6 - StepF15 -0.03352 0.0526 Inf -0.637 1.0000
StepF6 - StepF16 0.00628 0.0526 Inf 0.119 1.0000
StepF6 - StepF17 0.06177 0.0526 Inf 1.174 0.9995
StepF6 - StepF18 0.07121 0.0526 Inf 1.353 0.9972
StepF7 - StepF8 -0.06695 0.0526 Inf -1.272 0.9987
StepF7 - StepF9 -0.12220 0.0526 Inf -2.322 0.6673
StepF7 - StepF10 -0.12466 0.0526 Inf -2.369 0.6320
StepF7 - StepF11 -0.07346 0.0526 Inf -1.396 0.9959
StepF7 - StepF12 0.03823 0.0526 Inf 0.726 1.0000
StepF7 - StepF13 0.08598 0.0526 Inf 1.634 0.9776
StepF7 - StepF14 0.01367 0.0526 Inf 0.260 1.0000
StepF7 - StepF15 -0.01753 0.0526 Inf -0.333 1.0000
StepF7 - StepF16 0.02227 0.0526 Inf 0.423 1.0000
StepF7 - StepF17 0.07777 0.0526 Inf 1.478 0.9922
StepF7 - StepF18 0.08720 0.0526 Inf 1.657 0.9742
StepF8 - StepF9 -0.05524 0.0526 Inf -1.050 0.9999
StepF8 - StepF10 -0.05771 0.0526 Inf -1.096 0.9998
StepF8 - StepF11 -0.00651 0.0526 Inf -0.124 1.0000
StepF8 - StepF12 0.10518 0.0526 Inf 1.999 0.8705
StepF8 - StepF13 0.15293 0.0526 Inf 2.906 0.2490
StepF8 - StepF14 0.08062 0.0526 Inf 1.532 0.9884
StepF8 - StepF15 0.04943 0.0526 Inf 0.939 1.0000
StepF8 - StepF16 0.08923 0.0526 Inf 1.695 0.9678
StepF8 - StepF17 0.14472 0.0526 Inf 2.750 0.3457
StepF8 - StepF18 0.15415 0.0526 Inf 2.929 0.2362
StepF9 - StepF10 -0.00246 0.0526 Inf -0.047 1.0000
StepF9 - StepF11 0.04874 0.0526 Inf 0.926 1.0000
StepF9 - StepF12 0.16043 0.0526 Inf 3.048 0.1775
StepF9 - StepF13 0.20818 0.0526 Inf 3.956 0.0095
StepF9 - StepF14 0.13587 0.0526 Inf 2.582 0.4673
StepF9 - StepF15 0.10467 0.0526 Inf 1.989 0.8751
StepF9 - StepF16 0.14447 0.0526 Inf 2.745 0.3489
StepF9 - StepF17 0.19996 0.0526 Inf 3.800 0.0171
StepF9 - StepF18 0.20940 0.0526 Inf 3.979 0.0086
StepF10 - StepF11 0.05120 0.0526 Inf 0.973 1.0000
StepF10 - StepF12 0.16289 0.0526 Inf 3.095 0.1575
StepF10 - StepF13 0.21064 0.0526 Inf 4.002 0.0079
StepF10 - StepF14 0.13833 0.0526 Inf 2.628 0.4321
StepF10 - StepF15 0.10713 0.0526 Inf 2.036 0.8521
StepF10 - StepF16 0.14693 0.0526 Inf 2.792 0.3179
StepF10 - StepF17 0.20242 0.0526 Inf 3.846 0.0144
StepF10 - StepF18 0.21186 0.0526 Inf 4.026 0.0072
StepF11 - StepF12 0.11169 0.0526 Inf 2.122 0.8036
StepF11 - StepF13 0.15944 0.0526 Inf 3.030 0.1859
StepF11 - StepF14 0.08713 0.0526 Inf 1.656 0.9744
StepF11 - StepF15 0.05593 0.0526 Inf 1.063 0.9999
StepF11 - StepF16 0.09573 0.0526 Inf 1.819 0.9390
StepF11 - StepF17 0.15123 0.0526 Inf 2.873 0.2675
StepF11 - StepF18 0.16066 0.0526 Inf 3.053 0.1755
StepF12 - StepF13 0.04775 0.0526 Inf 0.907 1.0000
StepF12 - StepF14 -0.02456 0.0526 Inf -0.467 1.0000
StepF12 - StepF15 -0.05575 0.0526 Inf -1.059 0.9999
StepF12 - StepF16 -0.01595 0.0526 Inf -0.303 1.0000
StepF12 - StepF17 0.03954 0.0526 Inf 0.751 1.0000
StepF12 - StepF18 0.04897 0.0526 Inf 0.931 1.0000
StepF13 - StepF14 -0.07231 0.0526 Inf -1.374 0.9966
StepF13 - StepF15 -0.10351 0.0526 Inf -1.967 0.8852
StepF13 - StepF16 -0.06371 0.0526 Inf -1.211 0.9993
StepF13 - StepF17 -0.00821 0.0526 Inf -0.156 1.0000
StepF13 - StepF18 0.00122 0.0526 Inf 0.023 1.0000
StepF14 - StepF15 -0.03120 0.0526 Inf -0.593 1.0000
StepF14 - StepF16 0.00860 0.0526 Inf 0.163 1.0000
StepF14 - StepF17 0.06410 0.0526 Inf 1.218 0.9992
StepF14 - StepF18 0.07353 0.0526 Inf 1.397 0.9959
StepF15 - StepF16 0.03980 0.0526 Inf 0.756 1.0000
StepF15 - StepF17 0.09529 0.0526 Inf 1.811 0.9414
StepF15 - StepF18 0.10473 0.0526 Inf 1.990 0.8746
StepF16 - StepF17 0.05549 0.0526 Inf 1.054 0.9999
StepF16 - StepF18 0.06493 0.0526 Inf 1.234 0.9991
StepF17 - StepF18 0.00943 0.0526 Inf 0.179 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.19042 0.0526 Inf -3.618 0.0325
StepF1 - StepF3 -0.13133 0.0526 Inf -2.495 0.5337
StepF1 - StepF4 -0.02627 0.0526 Inf -0.499 1.0000
StepF1 - StepF5 0.06084 0.0526 Inf 1.156 0.9996
StepF1 - StepF6 0.01336 0.0526 Inf 0.254 1.0000
StepF1 - StepF7 -0.00263 0.0526 Inf -0.050 1.0000
StepF1 - StepF8 -0.06959 0.0526 Inf -1.322 0.9978
StepF1 - StepF9 -0.12483 0.0526 Inf -2.372 0.6295
StepF1 - StepF10 -0.12729 0.0526 Inf -2.419 0.5935
StepF1 - StepF11 -0.07609 0.0526 Inf -1.446 0.9939
StepF1 - StepF12 0.03560 0.0526 Inf 0.676 1.0000
StepF1 - StepF13 0.08335 0.0526 Inf 1.584 0.9836
StepF1 - StepF14 0.01104 0.0526 Inf 0.210 1.0000
StepF1 - StepF15 -0.02016 0.0526 Inf -0.383 1.0000
StepF1 - StepF16 0.01964 0.0526 Inf 0.373 1.0000
StepF1 - StepF17 0.07513 0.0526 Inf 1.428 0.9947
StepF1 - StepF18 0.08457 0.0526 Inf 1.607 0.9810
StepF2 - StepF3 0.05908 0.0526 Inf 1.123 0.9997
StepF2 - StepF4 0.16415 0.0526 Inf 3.119 0.1479
StepF2 - StepF5 0.25126 0.0526 Inf 4.774 0.0003
StepF2 - StepF6 0.20378 0.0526 Inf 3.872 0.0130
StepF2 - StepF7 0.18779 0.0526 Inf 3.568 0.0385
StepF2 - StepF8 0.12083 0.0526 Inf 2.296 0.6865
StepF2 - StepF9 0.06559 0.0526 Inf 1.246 0.9990
StepF2 - StepF10 0.06313 0.0526 Inf 1.199 0.9994
StepF2 - StepF11 0.11433 0.0526 Inf 2.172 0.7723
StepF2 - StepF12 0.22601 0.0526 Inf 4.294 0.0024
StepF2 - StepF13 0.27377 0.0526 Inf 5.202 <.0001
StepF2 - StepF14 0.20146 0.0526 Inf 3.828 0.0154
StepF2 - StepF15 0.17026 0.0526 Inf 3.235 0.1078
StepF2 - StepF16 0.21006 0.0526 Inf 3.991 0.0082
StepF2 - StepF17 0.26555 0.0526 Inf 5.046 0.0001
StepF2 - StepF18 0.27499 0.0526 Inf 5.225 <.0001
StepF3 - StepF4 0.10507 0.0526 Inf 1.996 0.8715
StepF3 - StepF5 0.19217 0.0526 Inf 3.651 0.0290
StepF3 - StepF6 0.14470 0.0526 Inf 2.749 0.3460
StepF3 - StepF7 0.12870 0.0526 Inf 2.445 0.5727
StepF3 - StepF8 0.06175 0.0526 Inf 1.173 0.9995
StepF3 - StepF9 0.00650 0.0526 Inf 0.124 1.0000
StepF3 - StepF10 0.00404 0.0526 Inf 0.077 1.0000
StepF3 - StepF11 0.05524 0.0526 Inf 1.050 0.9999
StepF3 - StepF12 0.16693 0.0526 Inf 3.172 0.1285
StepF3 - StepF13 0.21468 0.0526 Inf 4.079 0.0058
StepF3 - StepF14 0.14237 0.0526 Inf 2.705 0.3765
StepF3 - StepF15 0.11117 0.0526 Inf 2.112 0.8094
StepF3 - StepF16 0.15098 0.0526 Inf 2.869 0.2703
StepF3 - StepF17 0.20647 0.0526 Inf 3.923 0.0107
StepF3 - StepF18 0.21590 0.0526 Inf 4.102 0.0053
StepF4 - StepF5 0.08710 0.0526 Inf 1.655 0.9745
StepF4 - StepF6 0.03963 0.0526 Inf 0.753 1.0000
StepF4 - StepF7 0.02363 0.0526 Inf 0.449 1.0000
StepF4 - StepF8 -0.04332 0.0526 Inf -0.823 1.0000
StepF4 - StepF9 -0.09856 0.0526 Inf -1.873 0.9221
StepF4 - StepF10 -0.10103 0.0526 Inf -1.920 0.9049
StepF4 - StepF11 -0.04983 0.0526 Inf -0.947 1.0000
StepF4 - StepF12 0.06186 0.0526 Inf 1.175 0.9995
StepF4 - StepF13 0.10961 0.0526 Inf 2.083 0.8266
StepF4 - StepF14 0.03730 0.0526 Inf 0.709 1.0000
StepF4 - StepF15 0.00611 0.0526 Inf 0.116 1.0000
StepF4 - StepF16 0.04591 0.0526 Inf 0.872 1.0000
StepF4 - StepF17 0.10140 0.0526 Inf 1.927 0.9020
StepF4 - StepF18 0.11083 0.0526 Inf 2.106 0.8133
StepF5 - StepF6 -0.04748 0.0526 Inf -0.902 1.0000
StepF5 - StepF7 -0.06347 0.0526 Inf -1.206 0.9993
StepF5 - StepF8 -0.13042 0.0526 Inf -2.478 0.5472
StepF5 - StepF9 -0.18567 0.0526 Inf -3.528 0.0440
StepF5 - StepF10 -0.18813 0.0526 Inf -3.575 0.0377
StepF5 - StepF11 -0.13693 0.0526 Inf -2.602 0.4520
StepF5 - StepF12 -0.02524 0.0526 Inf -0.480 1.0000
StepF5 - StepF13 0.02251 0.0526 Inf 0.428 1.0000
StepF5 - StepF14 -0.04980 0.0526 Inf -0.946 1.0000
StepF5 - StepF15 -0.08100 0.0526 Inf -1.539 0.9879
StepF5 - StepF16 -0.04120 0.0526 Inf -0.783 1.0000
StepF5 - StepF17 0.01429 0.0526 Inf 0.272 1.0000
StepF5 - StepF18 0.02373 0.0526 Inf 0.451 1.0000
StepF6 - StepF7 -0.01599 0.0526 Inf -0.304 1.0000
StepF6 - StepF8 -0.08295 0.0526 Inf -1.576 0.9844
StepF6 - StepF9 -0.13819 0.0526 Inf -2.626 0.4341
StepF6 - StepF10 -0.14065 0.0526 Inf -2.673 0.3998
StepF6 - StepF11 -0.08945 0.0526 Inf -1.700 0.9670
StepF6 - StepF12 0.02223 0.0526 Inf 0.422 1.0000
StepF6 - StepF13 0.06999 0.0526 Inf 1.330 0.9977
StepF6 - StepF14 -0.00232 0.0526 Inf -0.044 1.0000
StepF6 - StepF15 -0.03352 0.0526 Inf -0.637 1.0000
StepF6 - StepF16 0.00628 0.0526 Inf 0.119 1.0000
StepF6 - StepF17 0.06177 0.0526 Inf 1.174 0.9995
StepF6 - StepF18 0.07121 0.0526 Inf 1.353 0.9972
StepF7 - StepF8 -0.06695 0.0526 Inf -1.272 0.9987
StepF7 - StepF9 -0.12220 0.0526 Inf -2.322 0.6673
StepF7 - StepF10 -0.12466 0.0526 Inf -2.369 0.6320
StepF7 - StepF11 -0.07346 0.0526 Inf -1.396 0.9959
StepF7 - StepF12 0.03823 0.0526 Inf 0.726 1.0000
StepF7 - StepF13 0.08598 0.0526 Inf 1.634 0.9776
StepF7 - StepF14 0.01367 0.0526 Inf 0.260 1.0000
StepF7 - StepF15 -0.01753 0.0526 Inf -0.333 1.0000
StepF7 - StepF16 0.02227 0.0526 Inf 0.423 1.0000
StepF7 - StepF17 0.07777 0.0526 Inf 1.478 0.9922
StepF7 - StepF18 0.08720 0.0526 Inf 1.657 0.9742
StepF8 - StepF9 -0.05524 0.0526 Inf -1.050 0.9999
StepF8 - StepF10 -0.05771 0.0526 Inf -1.096 0.9998
StepF8 - StepF11 -0.00651 0.0526 Inf -0.124 1.0000
StepF8 - StepF12 0.10518 0.0526 Inf 1.999 0.8705
StepF8 - StepF13 0.15293 0.0526 Inf 2.906 0.2490
StepF8 - StepF14 0.08062 0.0526 Inf 1.532 0.9884
StepF8 - StepF15 0.04943 0.0526 Inf 0.939 1.0000
StepF8 - StepF16 0.08923 0.0526 Inf 1.695 0.9678
StepF8 - StepF17 0.14472 0.0526 Inf 2.750 0.3457
StepF8 - StepF18 0.15415 0.0526 Inf 2.929 0.2362
StepF9 - StepF10 -0.00246 0.0526 Inf -0.047 1.0000
StepF9 - StepF11 0.04874 0.0526 Inf 0.926 1.0000
StepF9 - StepF12 0.16043 0.0526 Inf 3.048 0.1775
StepF9 - StepF13 0.20818 0.0526 Inf 3.956 0.0095
StepF9 - StepF14 0.13587 0.0526 Inf 2.582 0.4673
StepF9 - StepF15 0.10467 0.0526 Inf 1.989 0.8751
StepF9 - StepF16 0.14447 0.0526 Inf 2.745 0.3489
StepF9 - StepF17 0.19996 0.0526 Inf 3.800 0.0171
StepF9 - StepF18 0.20940 0.0526 Inf 3.979 0.0086
StepF10 - StepF11 0.05120 0.0526 Inf 0.973 1.0000
StepF10 - StepF12 0.16289 0.0526 Inf 3.095 0.1575
StepF10 - StepF13 0.21064 0.0526 Inf 4.002 0.0079
StepF10 - StepF14 0.13833 0.0526 Inf 2.628 0.4321
StepF10 - StepF15 0.10713 0.0526 Inf 2.036 0.8521
StepF10 - StepF16 0.14693 0.0526 Inf 2.792 0.3179
StepF10 - StepF17 0.20242 0.0526 Inf 3.846 0.0144
StepF10 - StepF18 0.21186 0.0526 Inf 4.026 0.0072
StepF11 - StepF12 0.11169 0.0526 Inf 2.122 0.8036
StepF11 - StepF13 0.15944 0.0526 Inf 3.030 0.1859
StepF11 - StepF14 0.08713 0.0526 Inf 1.656 0.9744
StepF11 - StepF15 0.05593 0.0526 Inf 1.063 0.9999
StepF11 - StepF16 0.09573 0.0526 Inf 1.819 0.9390
StepF11 - StepF17 0.15123 0.0526 Inf 2.873 0.2675
StepF11 - StepF18 0.16066 0.0526 Inf 3.053 0.1755
StepF12 - StepF13 0.04775 0.0526 Inf 0.907 1.0000
StepF12 - StepF14 -0.02456 0.0526 Inf -0.467 1.0000
StepF12 - StepF15 -0.05575 0.0526 Inf -1.059 0.9999
StepF12 - StepF16 -0.01595 0.0526 Inf -0.303 1.0000
StepF12 - StepF17 0.03954 0.0526 Inf 0.751 1.0000
StepF12 - StepF18 0.04897 0.0526 Inf 0.931 1.0000
StepF13 - StepF14 -0.07231 0.0526 Inf -1.374 0.9966
StepF13 - StepF15 -0.10351 0.0526 Inf -1.967 0.8852
StepF13 - StepF16 -0.06371 0.0526 Inf -1.211 0.9993
StepF13 - StepF17 -0.00821 0.0526 Inf -0.156 1.0000
StepF13 - StepF18 0.00122 0.0526 Inf 0.023 1.0000
StepF14 - StepF15 -0.03120 0.0526 Inf -0.593 1.0000
StepF14 - StepF16 0.00860 0.0526 Inf 0.163 1.0000
StepF14 - StepF17 0.06410 0.0526 Inf 1.218 0.9992
StepF14 - StepF18 0.07353 0.0526 Inf 1.397 0.9959
StepF15 - StepF16 0.03980 0.0526 Inf 0.756 1.0000
StepF15 - StepF17 0.09529 0.0526 Inf 1.811 0.9414
StepF15 - StepF18 0.10473 0.0526 Inf 1.990 0.8746
StepF16 - StepF17 0.05549 0.0526 Inf 1.054 0.9999
StepF16 - StepF18 0.06493 0.0526 Inf 1.234 0.9991
StepF17 - StepF18 0.00943 0.0526 Inf 0.179 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.19042 0.0526 Inf 3.618 0.0050
StepF3 - StepF2 -0.05908 0.0526 Inf -1.123 1.0000
StepF4 - StepF3 -0.10507 0.0526 Inf -1.996 0.6883
StepF5 - StepF4 -0.08710 0.0526 Inf -1.655 1.0000
StepF6 - StepF5 0.04748 0.0526 Inf 0.902 1.0000
StepF7 - StepF6 0.01599 0.0526 Inf 0.304 1.0000
StepF8 - StepF7 0.06695 0.0526 Inf 1.272 1.0000
StepF9 - StepF8 0.05524 0.0526 Inf 1.050 1.0000
StepF10 - StepF9 0.00246 0.0526 Inf 0.047 1.0000
StepF11 - StepF10 -0.05120 0.0526 Inf -0.973 1.0000
StepF12 - StepF11 -0.11169 0.0526 Inf -2.122 0.5412
StepF13 - StepF12 -0.04775 0.0526 Inf -0.907 1.0000
StepF14 - StepF13 0.07231 0.0526 Inf 1.374 1.0000
StepF15 - StepF14 0.03120 0.0526 Inf 0.593 1.0000
StepF16 - StepF15 -0.03980 0.0526 Inf -0.756 1.0000
StepF17 - StepF16 -0.05549 0.0526 Inf -1.054 1.0000
StepF18 - StepF17 -0.00943 0.0526 Inf -0.179 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.19042 0.0526 Inf 3.618 0.0050
StepF3 - StepF2 -0.05908 0.0526 Inf -1.123 1.0000
StepF4 - StepF3 -0.10507 0.0526 Inf -1.996 0.6883
StepF5 - StepF4 -0.08710 0.0526 Inf -1.655 1.0000
StepF6 - StepF5 0.04748 0.0526 Inf 0.902 1.0000
StepF7 - StepF6 0.01599 0.0526 Inf 0.304 1.0000
StepF8 - StepF7 0.06695 0.0526 Inf 1.272 1.0000
StepF9 - StepF8 0.05524 0.0526 Inf 1.050 1.0000
StepF10 - StepF9 0.00246 0.0526 Inf 0.047 1.0000
StepF11 - StepF10 -0.05120 0.0526 Inf -0.973 1.0000
StepF12 - StepF11 -0.11169 0.0526 Inf -2.122 0.5412
StepF13 - StepF12 -0.04775 0.0526 Inf -0.907 1.0000
StepF14 - StepF13 0.07231 0.0526 Inf 1.374 1.0000
StepF15 - StepF14 0.03120 0.0526 Inf 0.593 1.0000
StepF16 - StepF15 -0.03980 0.0526 Inf -0.756 1.0000
StepF17 - StepF16 -0.05549 0.0526 Inf -1.054 1.0000
StepF18 - StepF17 -0.00943 0.0526 Inf -0.179 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests
==============================
TEST | Block 5 | 18 steps | Axis Z
==============================
Type II Wald χ² (StepF & Accuracy):
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
StepF 134.3915 17 <2e-16 ***
Accuracy 0.1139 1 0.7357
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
EMMs per step | Accuracy:
Accuracy = 0:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.37 0.168 Inf 1.046 1.70
2 1.64 0.168 Inf 1.313 1.97
3 1.49 0.168 Inf 1.163 1.82
4 1.41 0.168 Inf 1.081 1.74
5 1.36 0.168 Inf 1.027 1.68
6 1.29 0.168 Inf 0.965 1.62
7 1.46 0.168 Inf 1.130 1.79
8 1.44 0.168 Inf 1.109 1.77
9 1.34 0.168 Inf 1.015 1.67
10 1.42 0.168 Inf 1.095 1.75
11 1.29 0.168 Inf 0.963 1.62
12 1.19 0.168 Inf 0.863 1.52
13 1.26 0.168 Inf 0.933 1.59
14 1.36 0.168 Inf 1.028 1.69
15 1.29 0.168 Inf 0.963 1.62
16 1.22 0.168 Inf 0.891 1.55
17 1.14 0.168 Inf 0.816 1.47
18 1.18 0.168 Inf 0.851 1.51
Accuracy = 1:
StepF emmean SE df asymp.LCL asymp.UCL
1 1.36 0.168 Inf 1.034 1.69
2 1.63 0.168 Inf 1.302 1.96
3 1.48 0.168 Inf 1.152 1.81
4 1.40 0.168 Inf 1.070 1.73
5 1.34 0.168 Inf 1.015 1.67
6 1.28 0.168 Inf 0.953 1.61
7 1.45 0.168 Inf 1.119 1.78
8 1.43 0.168 Inf 1.098 1.76
9 1.33 0.168 Inf 1.004 1.66
10 1.41 0.168 Inf 1.083 1.74
11 1.28 0.168 Inf 0.952 1.61
12 1.18 0.168 Inf 0.851 1.51
13 1.25 0.168 Inf 0.921 1.58
14 1.35 0.168 Inf 1.016 1.67
15 1.28 0.168 Inf 0.952 1.61
16 1.21 0.168 Inf 0.880 1.54
17 1.13 0.168 Inf 0.805 1.46
18 1.17 0.168 Inf 0.840 1.50
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
All-pairs (Tukey) among steps | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.267506 0.0627 Inf -4.264 0.0027
StepF1 - StepF3 -0.117392 0.0627 Inf -1.871 0.9226
StepF1 - StepF4 -0.035197 0.0627 Inf -0.561 1.0000
StepF1 - StepF5 0.019139 0.0627 Inf 0.305 1.0000
StepF1 - StepF6 0.081051 0.0627 Inf 1.292 0.9984
StepF1 - StepF7 -0.084321 0.0627 Inf -1.344 0.9974
StepF1 - StepF8 -0.063343 0.0627 Inf -1.010 0.9999
StepF1 - StepF9 0.030592 0.0627 Inf 0.488 1.0000
StepF1 - StepF10 -0.048773 0.0627 Inf -0.777 1.0000
StepF1 - StepF11 0.082387 0.0627 Inf 1.313 0.9980
StepF1 - StepF12 0.182847 0.0627 Inf 2.915 0.2441
StepF1 - StepF13 0.112883 0.0627 Inf 1.799 0.9445
StepF1 - StepF14 0.017971 0.0627 Inf 0.286 1.0000
StepF1 - StepF15 0.082635 0.0627 Inf 1.317 0.9979
StepF1 - StepF16 0.154461 0.0627 Inf 2.462 0.5597
StepF1 - StepF17 0.229657 0.0627 Inf 3.661 0.0281
StepF1 - StepF18 0.194802 0.0627 Inf 3.105 0.1534
StepF2 - StepF3 0.150114 0.0627 Inf 2.393 0.6134
StepF2 - StepF4 0.232309 0.0627 Inf 3.703 0.0242
StepF2 - StepF5 0.286645 0.0627 Inf 4.569 0.0007
StepF2 - StepF6 0.348557 0.0627 Inf 5.556 <.0001
StepF2 - StepF7 0.183186 0.0627 Inf 2.920 0.2411
StepF2 - StepF8 0.204163 0.0627 Inf 3.254 0.1020
StepF2 - StepF9 0.298098 0.0627 Inf 4.752 0.0003
StepF2 - StepF10 0.218733 0.0627 Inf 3.487 0.0503
StepF2 - StepF11 0.349892 0.0627 Inf 5.577 <.0001
StepF2 - StepF12 0.450353 0.0627 Inf 7.179 <.0001
StepF2 - StepF13 0.380389 0.0627 Inf 6.064 <.0001
StepF2 - StepF14 0.285477 0.0627 Inf 4.551 0.0008
StepF2 - StepF15 0.350141 0.0627 Inf 5.581 <.0001
StepF2 - StepF16 0.421967 0.0627 Inf 6.726 <.0001
StepF2 - StepF17 0.497163 0.0627 Inf 7.925 <.0001
StepF2 - StepF18 0.462308 0.0627 Inf 7.369 <.0001
StepF3 - StepF4 0.082195 0.0627 Inf 1.310 0.9981
StepF3 - StepF5 0.136532 0.0627 Inf 2.176 0.7696
StepF3 - StepF6 0.198443 0.0627 Inf 3.163 0.1315
StepF3 - StepF7 0.033072 0.0627 Inf 0.527 1.0000
StepF3 - StepF8 0.054049 0.0627 Inf 0.862 1.0000
StepF3 - StepF9 0.147985 0.0627 Inf 2.359 0.6394
StepF3 - StepF10 0.068620 0.0627 Inf 1.094 0.9998
StepF3 - StepF11 0.199779 0.0627 Inf 3.185 0.1241
StepF3 - StepF12 0.300239 0.0627 Inf 4.786 0.0002
StepF3 - StepF13 0.230275 0.0627 Inf 3.671 0.0271
StepF3 - StepF14 0.135364 0.0627 Inf 2.158 0.7816
StepF3 - StepF15 0.200028 0.0627 Inf 3.189 0.1227
StepF3 - StepF16 0.271853 0.0627 Inf 4.333 0.0020
StepF3 - StepF17 0.347050 0.0627 Inf 5.532 <.0001
StepF3 - StepF18 0.312194 0.0627 Inf 4.977 0.0001
StepF4 - StepF5 0.054337 0.0627 Inf 0.866 1.0000
StepF4 - StepF6 0.116248 0.0627 Inf 1.853 0.9286
StepF4 - StepF7 -0.049123 0.0627 Inf -0.783 1.0000
StepF4 - StepF8 -0.028146 0.0627 Inf -0.449 1.0000
StepF4 - StepF9 0.065790 0.0627 Inf 1.049 0.9999
StepF4 - StepF10 -0.013575 0.0627 Inf -0.216 1.0000
StepF4 - StepF11 0.117584 0.0627 Inf 1.874 0.9215
StepF4 - StepF12 0.218044 0.0627 Inf 3.476 0.0521
StepF4 - StepF13 0.148080 0.0627 Inf 2.360 0.6382
StepF4 - StepF14 0.053169 0.0627 Inf 0.848 1.0000
StepF4 - StepF15 0.117833 0.0627 Inf 1.878 0.9201
StepF4 - StepF16 0.189658 0.0627 Inf 3.023 0.1888
StepF4 - StepF17 0.264854 0.0627 Inf 4.222 0.0032
StepF4 - StepF18 0.229999 0.0627 Inf 3.666 0.0275
StepF5 - StepF6 0.061912 0.0627 Inf 0.987 1.0000
StepF5 - StepF7 -0.103460 0.0627 Inf -1.649 0.9754
StepF5 - StepF8 -0.082483 0.0627 Inf -1.315 0.9980
StepF5 - StepF9 0.011453 0.0627 Inf 0.183 1.0000
StepF5 - StepF10 -0.067912 0.0627 Inf -1.083 0.9998
StepF5 - StepF11 0.063247 0.0627 Inf 1.008 0.9999
StepF5 - StepF12 0.163707 0.0627 Inf 2.610 0.4462
StepF5 - StepF13 0.093743 0.0627 Inf 1.494 0.9912
StepF5 - StepF14 -0.001168 0.0627 Inf -0.019 1.0000
StepF5 - StepF15 0.063496 0.0627 Inf 1.012 0.9999
StepF5 - StepF16 0.135321 0.0627 Inf 2.157 0.7820
StepF5 - StepF17 0.210518 0.0627 Inf 3.356 0.0757
StepF5 - StepF18 0.175663 0.0627 Inf 2.800 0.3125
StepF6 - StepF7 -0.165371 0.0627 Inf -2.636 0.4264
StepF6 - StepF8 -0.144394 0.0627 Inf -2.302 0.6823
StepF6 - StepF9 -0.050459 0.0627 Inf -0.804 1.0000
StepF6 - StepF10 -0.129823 0.0627 Inf -2.069 0.8341
StepF6 - StepF11 0.001336 0.0627 Inf 0.021 1.0000
StepF6 - StepF12 0.101796 0.0627 Inf 1.623 0.9790
StepF6 - StepF13 0.031832 0.0627 Inf 0.507 1.0000
StepF6 - StepF14 -0.063080 0.0627 Inf -1.006 0.9999
StepF6 - StepF15 0.001584 0.0627 Inf 0.025 1.0000
StepF6 - StepF16 0.073410 0.0627 Inf 1.170 0.9995
StepF6 - StepF17 0.148606 0.0627 Inf 2.369 0.6319
StepF6 - StepF18 0.113751 0.0627 Inf 1.813 0.9407
StepF7 - StepF8 0.020977 0.0627 Inf 0.334 1.0000
StepF7 - StepF9 0.114913 0.0627 Inf 1.832 0.9353
StepF7 - StepF10 0.035548 0.0627 Inf 0.567 1.0000
StepF7 - StepF11 0.166707 0.0627 Inf 2.657 0.4108
StepF7 - StepF12 0.267167 0.0627 Inf 4.259 0.0027
StepF7 - StepF13 0.197203 0.0627 Inf 3.144 0.1387
StepF7 - StepF14 0.102292 0.0627 Inf 1.631 0.9780
StepF7 - StepF15 0.166956 0.0627 Inf 2.661 0.4079
StepF7 - StepF16 0.238781 0.0627 Inf 3.806 0.0167
StepF7 - StepF17 0.313978 0.0627 Inf 5.005 0.0001
StepF7 - StepF18 0.279122 0.0627 Inf 4.449 0.0012
StepF8 - StepF9 0.093936 0.0627 Inf 1.497 0.9910
StepF8 - StepF10 0.014571 0.0627 Inf 0.232 1.0000
StepF8 - StepF11 0.145730 0.0627 Inf 2.323 0.6665
StepF8 - StepF12 0.246190 0.0627 Inf 3.924 0.0107
StepF8 - StepF13 0.176226 0.0627 Inf 2.809 0.3068
StepF8 - StepF14 0.081314 0.0627 Inf 1.296 0.9983
StepF8 - StepF15 0.145979 0.0627 Inf 2.327 0.6635
StepF8 - StepF16 0.217804 0.0627 Inf 3.472 0.0528
StepF8 - StepF17 0.293000 0.0627 Inf 4.671 0.0004
StepF8 - StepF18 0.258145 0.0627 Inf 4.115 0.0050
StepF9 - StepF10 -0.079365 0.0627 Inf -1.265 0.9987
StepF9 - StepF11 0.051794 0.0627 Inf 0.826 1.0000
StepF9 - StepF12 0.152254 0.0627 Inf 2.427 0.5870
StepF9 - StepF13 0.082291 0.0627 Inf 1.312 0.9980
StepF9 - StepF14 -0.012621 0.0627 Inf -0.201 1.0000
StepF9 - StepF15 0.052043 0.0627 Inf 0.830 1.0000
StepF9 - StepF16 0.123869 0.0627 Inf 1.975 0.8817
StepF9 - StepF17 0.199065 0.0627 Inf 3.173 0.1280
StepF9 - StepF18 0.164210 0.0627 Inf 2.618 0.4402
StepF10 - StepF11 0.131159 0.0627 Inf 2.091 0.8221
StepF10 - StepF12 0.231619 0.0627 Inf 3.692 0.0251
StepF10 - StepF13 0.161655 0.0627 Inf 2.577 0.4709
StepF10 - StepF14 0.066744 0.0627 Inf 1.064 0.9999
StepF10 - StepF15 0.131408 0.0627 Inf 2.095 0.8198
StepF10 - StepF16 0.203233 0.0627 Inf 3.240 0.1064
StepF10 - StepF17 0.278430 0.0627 Inf 4.438 0.0013
StepF10 - StepF18 0.243574 0.0627 Inf 3.883 0.0125
StepF11 - StepF12 0.100460 0.0627 Inf 1.601 0.9817
StepF11 - StepF13 0.030496 0.0627 Inf 0.486 1.0000
StepF11 - StepF14 -0.064415 0.0627 Inf -1.027 0.9999
StepF11 - StepF15 0.000249 0.0627 Inf 0.004 1.0000
StepF11 - StepF16 0.072074 0.0627 Inf 1.149 0.9996
StepF11 - StepF17 0.147271 0.0627 Inf 2.348 0.6480
StepF11 - StepF18 0.112416 0.0627 Inf 1.792 0.9465
StepF12 - StepF13 -0.069964 0.0627 Inf -1.115 0.9998
StepF12 - StepF14 -0.164876 0.0627 Inf -2.628 0.4323
StepF12 - StepF15 -0.100211 0.0627 Inf -1.597 0.9821
StepF12 - StepF16 -0.028386 0.0627 Inf -0.452 1.0000
StepF12 - StepF17 0.046810 0.0627 Inf 0.746 1.0000
StepF12 - StepF18 0.011955 0.0627 Inf 0.191 1.0000
StepF13 - StepF14 -0.094911 0.0627 Inf -1.513 0.9899
StepF13 - StepF15 -0.030248 0.0627 Inf -0.482 1.0000
StepF13 - StepF16 0.041578 0.0627 Inf 0.663 1.0000
StepF13 - StepF17 0.116774 0.0627 Inf 1.861 0.9259
StepF13 - StepF18 0.081919 0.0627 Inf 1.306 0.9981
StepF14 - StepF15 0.064664 0.0627 Inf 1.031 0.9999
StepF14 - StepF16 0.136490 0.0627 Inf 2.176 0.7701
StepF14 - StepF17 0.211686 0.0627 Inf 3.374 0.0716
StepF14 - StepF18 0.176831 0.0627 Inf 2.819 0.3007
StepF15 - StepF16 0.071826 0.0627 Inf 1.145 0.9997
StepF15 - StepF17 0.147022 0.0627 Inf 2.344 0.6510
StepF15 - StepF18 0.112167 0.0627 Inf 1.788 0.9476
StepF16 - StepF17 0.075196 0.0627 Inf 1.199 0.9994
StepF16 - StepF18 0.040341 0.0627 Inf 0.643 1.0000
StepF17 - StepF18 -0.034855 0.0627 Inf -0.556 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF1 - StepF2 -0.267506 0.0627 Inf -4.264 0.0027
StepF1 - StepF3 -0.117392 0.0627 Inf -1.871 0.9226
StepF1 - StepF4 -0.035197 0.0627 Inf -0.561 1.0000
StepF1 - StepF5 0.019139 0.0627 Inf 0.305 1.0000
StepF1 - StepF6 0.081051 0.0627 Inf 1.292 0.9984
StepF1 - StepF7 -0.084321 0.0627 Inf -1.344 0.9974
StepF1 - StepF8 -0.063343 0.0627 Inf -1.010 0.9999
StepF1 - StepF9 0.030592 0.0627 Inf 0.488 1.0000
StepF1 - StepF10 -0.048773 0.0627 Inf -0.777 1.0000
StepF1 - StepF11 0.082387 0.0627 Inf 1.313 0.9980
StepF1 - StepF12 0.182847 0.0627 Inf 2.915 0.2441
StepF1 - StepF13 0.112883 0.0627 Inf 1.799 0.9445
StepF1 - StepF14 0.017971 0.0627 Inf 0.286 1.0000
StepF1 - StepF15 0.082635 0.0627 Inf 1.317 0.9979
StepF1 - StepF16 0.154461 0.0627 Inf 2.462 0.5597
StepF1 - StepF17 0.229657 0.0627 Inf 3.661 0.0281
StepF1 - StepF18 0.194802 0.0627 Inf 3.105 0.1534
StepF2 - StepF3 0.150114 0.0627 Inf 2.393 0.6134
StepF2 - StepF4 0.232309 0.0627 Inf 3.703 0.0242
StepF2 - StepF5 0.286645 0.0627 Inf 4.569 0.0007
StepF2 - StepF6 0.348557 0.0627 Inf 5.556 <.0001
StepF2 - StepF7 0.183186 0.0627 Inf 2.920 0.2411
StepF2 - StepF8 0.204163 0.0627 Inf 3.254 0.1020
StepF2 - StepF9 0.298098 0.0627 Inf 4.752 0.0003
StepF2 - StepF10 0.218733 0.0627 Inf 3.487 0.0503
StepF2 - StepF11 0.349892 0.0627 Inf 5.577 <.0001
StepF2 - StepF12 0.450353 0.0627 Inf 7.179 <.0001
StepF2 - StepF13 0.380389 0.0627 Inf 6.064 <.0001
StepF2 - StepF14 0.285477 0.0627 Inf 4.551 0.0008
StepF2 - StepF15 0.350141 0.0627 Inf 5.581 <.0001
StepF2 - StepF16 0.421967 0.0627 Inf 6.726 <.0001
StepF2 - StepF17 0.497163 0.0627 Inf 7.925 <.0001
StepF2 - StepF18 0.462308 0.0627 Inf 7.369 <.0001
StepF3 - StepF4 0.082195 0.0627 Inf 1.310 0.9981
StepF3 - StepF5 0.136532 0.0627 Inf 2.176 0.7696
StepF3 - StepF6 0.198443 0.0627 Inf 3.163 0.1315
StepF3 - StepF7 0.033072 0.0627 Inf 0.527 1.0000
StepF3 - StepF8 0.054049 0.0627 Inf 0.862 1.0000
StepF3 - StepF9 0.147985 0.0627 Inf 2.359 0.6394
StepF3 - StepF10 0.068620 0.0627 Inf 1.094 0.9998
StepF3 - StepF11 0.199779 0.0627 Inf 3.185 0.1241
StepF3 - StepF12 0.300239 0.0627 Inf 4.786 0.0002
StepF3 - StepF13 0.230275 0.0627 Inf 3.671 0.0271
StepF3 - StepF14 0.135364 0.0627 Inf 2.158 0.7816
StepF3 - StepF15 0.200028 0.0627 Inf 3.189 0.1227
StepF3 - StepF16 0.271853 0.0627 Inf 4.333 0.0020
StepF3 - StepF17 0.347050 0.0627 Inf 5.532 <.0001
StepF3 - StepF18 0.312194 0.0627 Inf 4.977 0.0001
StepF4 - StepF5 0.054337 0.0627 Inf 0.866 1.0000
StepF4 - StepF6 0.116248 0.0627 Inf 1.853 0.9286
StepF4 - StepF7 -0.049123 0.0627 Inf -0.783 1.0000
StepF4 - StepF8 -0.028146 0.0627 Inf -0.449 1.0000
StepF4 - StepF9 0.065790 0.0627 Inf 1.049 0.9999
StepF4 - StepF10 -0.013575 0.0627 Inf -0.216 1.0000
StepF4 - StepF11 0.117584 0.0627 Inf 1.874 0.9215
StepF4 - StepF12 0.218044 0.0627 Inf 3.476 0.0521
StepF4 - StepF13 0.148080 0.0627 Inf 2.360 0.6382
StepF4 - StepF14 0.053169 0.0627 Inf 0.848 1.0000
StepF4 - StepF15 0.117833 0.0627 Inf 1.878 0.9201
StepF4 - StepF16 0.189658 0.0627 Inf 3.023 0.1888
StepF4 - StepF17 0.264854 0.0627 Inf 4.222 0.0032
StepF4 - StepF18 0.229999 0.0627 Inf 3.666 0.0275
StepF5 - StepF6 0.061912 0.0627 Inf 0.987 1.0000
StepF5 - StepF7 -0.103460 0.0627 Inf -1.649 0.9754
StepF5 - StepF8 -0.082483 0.0627 Inf -1.315 0.9980
StepF5 - StepF9 0.011453 0.0627 Inf 0.183 1.0000
StepF5 - StepF10 -0.067912 0.0627 Inf -1.083 0.9998
StepF5 - StepF11 0.063247 0.0627 Inf 1.008 0.9999
StepF5 - StepF12 0.163707 0.0627 Inf 2.610 0.4462
StepF5 - StepF13 0.093743 0.0627 Inf 1.494 0.9912
StepF5 - StepF14 -0.001168 0.0627 Inf -0.019 1.0000
StepF5 - StepF15 0.063496 0.0627 Inf 1.012 0.9999
StepF5 - StepF16 0.135321 0.0627 Inf 2.157 0.7820
StepF5 - StepF17 0.210518 0.0627 Inf 3.356 0.0757
StepF5 - StepF18 0.175663 0.0627 Inf 2.800 0.3125
StepF6 - StepF7 -0.165371 0.0627 Inf -2.636 0.4264
StepF6 - StepF8 -0.144394 0.0627 Inf -2.302 0.6823
StepF6 - StepF9 -0.050459 0.0627 Inf -0.804 1.0000
StepF6 - StepF10 -0.129823 0.0627 Inf -2.069 0.8341
StepF6 - StepF11 0.001336 0.0627 Inf 0.021 1.0000
StepF6 - StepF12 0.101796 0.0627 Inf 1.623 0.9790
StepF6 - StepF13 0.031832 0.0627 Inf 0.507 1.0000
StepF6 - StepF14 -0.063080 0.0627 Inf -1.006 0.9999
StepF6 - StepF15 0.001584 0.0627 Inf 0.025 1.0000
StepF6 - StepF16 0.073410 0.0627 Inf 1.170 0.9995
StepF6 - StepF17 0.148606 0.0627 Inf 2.369 0.6319
StepF6 - StepF18 0.113751 0.0627 Inf 1.813 0.9407
StepF7 - StepF8 0.020977 0.0627 Inf 0.334 1.0000
StepF7 - StepF9 0.114913 0.0627 Inf 1.832 0.9353
StepF7 - StepF10 0.035548 0.0627 Inf 0.567 1.0000
StepF7 - StepF11 0.166707 0.0627 Inf 2.657 0.4108
StepF7 - StepF12 0.267167 0.0627 Inf 4.259 0.0027
StepF7 - StepF13 0.197203 0.0627 Inf 3.144 0.1387
StepF7 - StepF14 0.102292 0.0627 Inf 1.631 0.9780
StepF7 - StepF15 0.166956 0.0627 Inf 2.661 0.4079
StepF7 - StepF16 0.238781 0.0627 Inf 3.806 0.0167
StepF7 - StepF17 0.313978 0.0627 Inf 5.005 0.0001
StepF7 - StepF18 0.279122 0.0627 Inf 4.449 0.0012
StepF8 - StepF9 0.093936 0.0627 Inf 1.497 0.9910
StepF8 - StepF10 0.014571 0.0627 Inf 0.232 1.0000
StepF8 - StepF11 0.145730 0.0627 Inf 2.323 0.6665
StepF8 - StepF12 0.246190 0.0627 Inf 3.924 0.0107
StepF8 - StepF13 0.176226 0.0627 Inf 2.809 0.3068
StepF8 - StepF14 0.081314 0.0627 Inf 1.296 0.9983
StepF8 - StepF15 0.145979 0.0627 Inf 2.327 0.6635
StepF8 - StepF16 0.217804 0.0627 Inf 3.472 0.0528
StepF8 - StepF17 0.293000 0.0627 Inf 4.671 0.0004
StepF8 - StepF18 0.258145 0.0627 Inf 4.115 0.0050
StepF9 - StepF10 -0.079365 0.0627 Inf -1.265 0.9987
StepF9 - StepF11 0.051794 0.0627 Inf 0.826 1.0000
StepF9 - StepF12 0.152254 0.0627 Inf 2.427 0.5870
StepF9 - StepF13 0.082291 0.0627 Inf 1.312 0.9980
StepF9 - StepF14 -0.012621 0.0627 Inf -0.201 1.0000
StepF9 - StepF15 0.052043 0.0627 Inf 0.830 1.0000
StepF9 - StepF16 0.123869 0.0627 Inf 1.975 0.8817
StepF9 - StepF17 0.199065 0.0627 Inf 3.173 0.1280
StepF9 - StepF18 0.164210 0.0627 Inf 2.618 0.4402
StepF10 - StepF11 0.131159 0.0627 Inf 2.091 0.8221
StepF10 - StepF12 0.231619 0.0627 Inf 3.692 0.0251
StepF10 - StepF13 0.161655 0.0627 Inf 2.577 0.4709
StepF10 - StepF14 0.066744 0.0627 Inf 1.064 0.9999
StepF10 - StepF15 0.131408 0.0627 Inf 2.095 0.8198
StepF10 - StepF16 0.203233 0.0627 Inf 3.240 0.1064
StepF10 - StepF17 0.278430 0.0627 Inf 4.438 0.0013
StepF10 - StepF18 0.243574 0.0627 Inf 3.883 0.0125
StepF11 - StepF12 0.100460 0.0627 Inf 1.601 0.9817
StepF11 - StepF13 0.030496 0.0627 Inf 0.486 1.0000
StepF11 - StepF14 -0.064415 0.0627 Inf -1.027 0.9999
StepF11 - StepF15 0.000249 0.0627 Inf 0.004 1.0000
StepF11 - StepF16 0.072074 0.0627 Inf 1.149 0.9996
StepF11 - StepF17 0.147271 0.0627 Inf 2.348 0.6480
StepF11 - StepF18 0.112416 0.0627 Inf 1.792 0.9465
StepF12 - StepF13 -0.069964 0.0627 Inf -1.115 0.9998
StepF12 - StepF14 -0.164876 0.0627 Inf -2.628 0.4323
StepF12 - StepF15 -0.100211 0.0627 Inf -1.597 0.9821
StepF12 - StepF16 -0.028386 0.0627 Inf -0.452 1.0000
StepF12 - StepF17 0.046810 0.0627 Inf 0.746 1.0000
StepF12 - StepF18 0.011955 0.0627 Inf 0.191 1.0000
StepF13 - StepF14 -0.094911 0.0627 Inf -1.513 0.9899
StepF13 - StepF15 -0.030248 0.0627 Inf -0.482 1.0000
StepF13 - StepF16 0.041578 0.0627 Inf 0.663 1.0000
StepF13 - StepF17 0.116774 0.0627 Inf 1.861 0.9259
StepF13 - StepF18 0.081919 0.0627 Inf 1.306 0.9981
StepF14 - StepF15 0.064664 0.0627 Inf 1.031 0.9999
StepF14 - StepF16 0.136490 0.0627 Inf 2.176 0.7701
StepF14 - StepF17 0.211686 0.0627 Inf 3.374 0.0716
StepF14 - StepF18 0.176831 0.0627 Inf 2.819 0.3007
StepF15 - StepF16 0.071826 0.0627 Inf 1.145 0.9997
StepF15 - StepF17 0.147022 0.0627 Inf 2.344 0.6510
StepF15 - StepF18 0.112167 0.0627 Inf 1.788 0.9476
StepF16 - StepF17 0.075196 0.0627 Inf 1.199 0.9994
StepF16 - StepF18 0.040341 0.0627 Inf 0.643 1.0000
StepF17 - StepF18 -0.034855 0.0627 Inf -0.556 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 18 estimates
Adjacent steps (consec; Holm) | Accuracy:
Accuracy = 0:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2675 0.0627 Inf 4.264 0.0003
StepF3 - StepF2 -0.1501 0.0627 Inf -2.393 0.2507
StepF4 - StepF3 -0.0822 0.0627 Inf -1.310 1.0000
StepF5 - StepF4 -0.0543 0.0627 Inf -0.866 1.0000
StepF6 - StepF5 -0.0619 0.0627 Inf -0.987 1.0000
StepF7 - StepF6 0.1654 0.0627 Inf 2.636 0.1342
StepF8 - StepF7 -0.0210 0.0627 Inf -0.334 1.0000
StepF9 - StepF8 -0.0939 0.0627 Inf -1.497 1.0000
StepF10 - StepF9 0.0794 0.0627 Inf 1.265 1.0000
StepF11 - StepF10 -0.1312 0.0627 Inf -2.091 0.5117
StepF12 - StepF11 -0.1005 0.0627 Inf -1.601 1.0000
StepF13 - StepF12 0.0700 0.0627 Inf 1.115 1.0000
StepF14 - StepF13 0.0949 0.0627 Inf 1.513 1.0000
StepF15 - StepF14 -0.0647 0.0627 Inf -1.031 1.0000
StepF16 - StepF15 -0.0718 0.0627 Inf -1.145 1.0000
StepF17 - StepF16 -0.0752 0.0627 Inf -1.199 1.0000
StepF18 - StepF17 0.0349 0.0627 Inf 0.556 1.0000
Accuracy = 1:
contrast estimate SE df z.ratio p.value
StepF2 - StepF1 0.2675 0.0627 Inf 4.264 0.0003
StepF3 - StepF2 -0.1501 0.0627 Inf -2.393 0.2507
StepF4 - StepF3 -0.0822 0.0627 Inf -1.310 1.0000
StepF5 - StepF4 -0.0543 0.0627 Inf -0.866 1.0000
StepF6 - StepF5 -0.0619 0.0627 Inf -0.987 1.0000
StepF7 - StepF6 0.1654 0.0627 Inf 2.636 0.1342
StepF8 - StepF7 -0.0210 0.0627 Inf -0.334 1.0000
StepF9 - StepF8 -0.0939 0.0627 Inf -1.497 1.0000
StepF10 - StepF9 0.0794 0.0627 Inf 1.265 1.0000
StepF11 - StepF10 -0.1312 0.0627 Inf -2.091 0.5117
StepF12 - StepF11 -0.1005 0.0627 Inf -1.601 1.0000
StepF13 - StepF12 0.0700 0.0627 Inf 1.115 1.0000
StepF14 - StepF13 0.0949 0.0627 Inf 1.513 1.0000
StepF15 - StepF14 -0.0647 0.0627 Inf -1.031 1.0000
StepF16 - StepF15 -0.0718 0.0627 Inf -1.145 1.0000
StepF17 - StepF16 -0.0752 0.0627 Inf -1.199 1.0000
StepF18 - StepF17 0.0349 0.0627 Inf 0.556 1.0000
Degrees-of-freedom method: asymptotic
P value adjustment: holm method for 17 tests 3.2 Concatenation plots
# ==== TRAINING (Blocks 1–3): Step-wise EMM ± SD (Correct-only) + All-axes overlay ====
suppressPackageStartupMessages({
library(dplyr); library(ggplot2); library(lme4); library(emmeans); library(patchwork)
})
emm_options(lmer.df = "asymptotic")
.get_emm_sd_correct <- function(df_axis) {
if (nrow(df_axis) == 0) return(NULL)
dd <- df_axis %>%
filter(as.character(Accuracy) == "1") %>%
mutate(
StepF = factor(Step, levels = sort(unique(Step))),
subject = factor(subject),
trial_id = factor(trial_id)
)
if (nrow(dd) == 0) return(NULL)
m <- suppressWarnings(lmer(RMS ~ StepF + (1|subject) + (1|trial_id), data = dd, REML = TRUE))
em_df <- as.data.frame(emmeans(m, ~ StepF)) %>%
transmute(Step = as.numeric(as.character(StepF)),
emmean = emmean)
sd_df <- dd %>%
group_by(StepF) %>%
summarise(sd = sd(RMS, na.rm = TRUE), .groups = "drop") %>%
transmute(Step = as.numeric(as.character(StepF)), sd = sd)
em_df %>%
left_join(sd_df, by = "Step") %>%
mutate(ymin = pmax(0, emmean - sd),
ymax = emmean + sd)
}
.plot_block_stepwise_sd_correct <- function(df_block, block_title) {
axes_map <- c("x"="X","y"="Y","z"="Z")
out <- lapply(names(axes_map), function(ax) {
tbl <- .get_emm_sd_correct(df_block %>% filter(Axis == ax))
if (is.null(tbl)) return(NULL)
tbl %>% mutate(Axis = axes_map[[ax]])
})
emms_tbl <- bind_rows(out)
if (nrow(emms_tbl) == 0) return(invisible(NULL))
# (1) Faceted by Axis (as before)
p_facets <- ggplot(emms_tbl, aes(x = Step, y = emmean)) +
geom_ribbon(aes(ymin = ymin, ymax = ymax), alpha = 0.18) +
geom_line(size = 0.9) +
geom_point(size = 1.2) +
facet_wrap(~ Axis, nrow = 1, scales = "free_y") +
labs(title = paste0(block_title, " — Step-wise EMMs (±SD) — Correct trials"),
x = "Step", y = "EMM RMS") +
theme_classic() +
theme(legend.position = "none")
# (2) All axes in one panel
p_overlay <- ggplot(emms_tbl, aes(x = Step, y = emmean, color = Axis, fill = Axis, group = Axis)) +
geom_ribbon(aes(ymin = ymin, ymax = ymax), alpha = 0.15, color = NA) +
geom_line(size = 0.9) +
geom_point(size = 1.2) +
labs(title = paste0(block_title, " — Step-wise EMMs (±SD) — Correct trials (X/Y/Z overlaid)"),
x = "Step", y = "EMM RMS") +
theme_classic() +
theme(legend.position = "bottom")
list(facets = p_facets, overlay = p_overlay)
}
# Render for each training block
res_b1 <- .plot_block_stepwise_sd_correct(stepwise_6, "Block 1 (6 steps)")Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.res_b2 <- .plot_block_stepwise_sd_correct(stepwise_12, "Block 2 (12 steps)")
res_b3 <- .plot_block_stepwise_sd_correct(stepwise_18, "Block 3 (18 steps)")
if (!is.null(res_b1)) { print(res_b1$facets); print(res_b1$overlay) }
if (!is.null(res_b2)) { print(res_b2$facets); print(res_b2$overlay) }
if (!is.null(res_b3)) { print(res_b3$facets); print(res_b3$overlay) }
# ==== TEST (Blocks 4–5): Step-wise EMM ± SD (Correct-only) + All-axes overlay per seq length ====
suppressPackageStartupMessages({
library(dplyr); library(ggplot2); library(lme4); library(emmeans); library(patchwork)
})
emm_options(lmer.df = "asymptotic")
.get_emm_sd_correct <- function(df_axis) {
if (nrow(df_axis) == 0) return(NULL)
dd <- df_axis %>%
filter(as.character(Accuracy) == "1") %>%
mutate(
StepF = factor(Step, levels = sort(unique(Step))),
subject = factor(subject),
trial_id = factor(trial_id)
)
if (nrow(dd) == 0) return(NULL)
m <- suppressWarnings(lmer(RMS ~ StepF + (1|subject) + (1|trial_id), data = dd, REML = TRUE))
em_df <- as.data.frame(emmeans(m, ~ StepF)) %>%
transmute(Step = as.numeric(as.character(StepF)),
emmean = emmean)
sd_df <- dd %>%
group_by(StepF) %>%
summarise(sd = sd(RMS, na.rm = TRUE), .groups = "drop") %>%
transmute(Step = as.numeric(as.character(StepF)), sd = sd)
em_df %>%
left_join(sd_df, by = "Step") %>%
mutate(ymin = pmax(0, emmean - sd),
ymax = emmean + sd)
}
.plot_block_len_sd_correct <- function(df_block, title_prefix) {
axes_map <- c("x"="X","y"="Y","z"="Z")
out <- lapply(names(axes_map), function(ax) {
tbl <- .get_emm_sd_correct(df_block %>% filter(Axis == ax))
if (is.null(tbl)) return(NULL)
tbl %>% mutate(Axis = axes_map[[ax]])
})
emms_tbl <- bind_rows(out)
if (nrow(emms_tbl) == 0) return(invisible(NULL))
# (1) Faceted by Axis (as before)
p_facets <- ggplot(emms_tbl, aes(x = Step, y = emmean)) +
geom_ribbon(aes(ymin = ymin, ymax = ymax), alpha = 0.18) +
geom_line(size = 0.9) +
geom_point(size = 1.2) +
facet_wrap(~ Axis, nrow = 1, scales = "free_y") +
labs(title = paste0(title_prefix, " — Step-wise EMMs (±SD) — Correct trials"),
x = "Step", y = "EMM RMS") +
theme_classic() +
theme(legend.position = "none")
# (2) All axes in one panel
p_overlay <- ggplot(emms_tbl, aes(x = Step, y = emmean, color = Axis, fill = Axis, group = Axis)) +
geom_ribbon(aes(ymin = ymin, ymax = ymax), alpha = 0.15, color = NA) +
geom_line(size = 0.9) +
geom_point(size = 1.2) +
labs(title = paste0(title_prefix, " — Step-wise EMMs (±SD) — Correct trials (X/Y/Z overlaid)"),
x = "Step", y = "EMM RMS") +
theme_classic() +
theme(legend.position = "bottom")
list(facets = p_facets, overlay = p_overlay)
}
# Block 4
res_b4_6 <- .plot_block_len_sd_correct(sw_b4_6, "Block 4 — 6 steps")
res_b4_12 <- .plot_block_len_sd_correct(sw_b4_12, "Block 4 — 12 steps")
res_b4_18 <- .plot_block_len_sd_correct(sw_b4_18, "Block 4 — 18 steps")
if (!is.null(res_b4_6)) { print(res_b4_6$facets); print(res_b4_6$overlay) }
if (!is.null(res_b4_12)) { print(res_b4_12$facets); print(res_b4_12$overlay) }
if (!is.null(res_b4_18)) { print(res_b4_18$facets); print(res_b4_18$overlay) }
# Block 5
res_b5_6 <- .plot_block_len_sd_correct(sw_b5_6, "Block 5 — 6 steps")
res_b5_12 <- .plot_block_len_sd_correct(sw_b5_12, "Block 5 — 12 steps")
res_b5_18 <- .plot_block_len_sd_correct(sw_b5_18, "Block 5 — 18 steps")
if (!is.null(res_b5_6)) { print(res_b5_6$facets); print(res_b5_6$overlay) }
if (!is.null(res_b5_12)) { print(res_b5_12$facets); print(res_b5_12$overlay) }
if (!is.null(res_b5_18)) { print(res_b5_18$facets); print(res_b5_18$overlay) }
#additional analysis comparing which axis shows the highest variability
# ==== #1.3bis: RMS differences among axes (X/Y/Z) across blocks ====
# RMS ~ Axis * Block + Accuracy + (1 | subject) + (1 | Trial)
# and EMMs + Tukey pairwise comparisons for Axis (overall and per block).
suppressPackageStartupMessages({
library(dplyr); library(tidyr)
library(lme4); library(lmerTest)
library(emmeans); library(car)
})
emm_options(lmer.df = "asymptotic")
# Prepare long format once
axes_long <- rms_combined %>%
dplyr::select(subject, Trial, Block, phase, Accuracy, rms_x, rms_y, rms_z) %>%
tidyr::pivot_longer(
cols = c(rms_x, rms_y, rms_z),
names_to = "Axis",
values_to = "RMS"
) %>%
mutate(
Axis = dplyr::recode(Axis, rms_x = "X", rms_y = "Y", rms_z = "Z"),
Axis = factor(Axis, levels = c("X","Y","Z")),
Block = factor(Block), # already factor upstream
phase = factor(phase, levels = c("Preparation","Execution"))
) %>%
tidyr::drop_na(RMS) %>%
droplevels()
analyze_axes_vs_blocks <- function(df, label = "OVERALL (collapsed across phase)") {
cat("\n\n==============================\n",
"AXES × BLOCKS — ", label,
"\n==============================\n", sep = "")
m <- lmer(RMS ~ Axis * Block + Accuracy + (1 | subject) + (1 | Trial), data = df, REML = TRUE)
cat("\n--- Model Summary (lmerTest; Satterthwaite t-tests) ---\n")
print(summary(m))
cat("\n--- lmerTest ANOVA (F-tests; Satterthwaite) ---\n")
print(anova(m))
cat("\n--- Type II Wald χ² (car::Anova) ---\n")
print(car::Anova(m, type = 2, test.statistic = "Chisq"))
cat("\n--- Type III Wald χ² (car::Anova; sum contrasts) ---\n")
print(car::Anova(m, type = 3, test.statistic = "Chisq"))
# EMMs for Axis (averaged over Blocks & Accuracy levels present)
em_axis <- emmeans(m, ~ Axis)
cat("\n--- EMMs by Axis (averaged over Blocks) ---\n")
print(summary(em_axis))
cat("\n--- Pairwise (Tukey) Axis comparisons (overall) ---\n")
print(pairs(em_axis, adjust = "tukey"))
# Simple effects: Axis differences within each Block
em_axis_by_block <- emmeans(m, ~ Axis | Block)
cat("\n--- EMMs by Axis within each Block ---\n")
print(summary(em_axis_by_block))
cat("\n--- Pairwise (Tukey) Axis comparisons within each Block ---\n")
print(pairs(em_axis_by_block, adjust = "tukey"))
invisible(TRUE)
}
# 1) Collapsed across phase (overall)
analyze_axes_vs_blocks(axes_long, label = "OVERALL")
==============================
AXES × BLOCKS — OVERALL
==============================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Axis * Block + Accuracy + (1 | subject) + (1 | Trial)
Data: df
REML criterion at convergence: 54387.8
Scaled residuals:
Min 1Q Median 3Q Max
-2.2450 -0.7332 -0.0719 0.5559 13.7440
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.001358 0.03684
subject (Intercept) 0.029239 0.17099
Residual 0.278967 0.52817
Number of obs: 34656, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 4.891e-01 4.076e-02 1.761e+01 12.000 6.59e-10 ***
Axis1 -9.296e-02 4.029e-03 3.457e+04 -23.073 < 2e-16 ***
Axis2 -7.535e-02 4.029e-03 3.457e+04 -18.701 < 2e-16 ***
Block1 1.759e-02 6.125e-03 3.462e+04 2.871 0.00409 **
Block2 2.802e-02 5.699e-03 3.462e+04 4.916 8.88e-07 ***
Block3 -1.481e-02 5.738e-03 3.442e+04 -2.580 0.00987 **
Block4 2.674e-02 5.740e-03 3.461e+04 4.659 3.19e-06 ***
Accuracy1 -2.407e-02 3.040e-03 3.329e+04 -7.915 2.54e-15 ***
Axis1:Block1 1.025e-03 8.502e-03 3.457e+04 0.121 0.90405
Axis2:Block1 6.267e-03 8.502e-03 3.457e+04 0.737 0.46102
Axis1:Block2 -1.060e-02 8.044e-03 3.457e+04 -1.317 0.18772
Axis2:Block2 -2.157e-03 8.044e-03 3.457e+04 -0.268 0.78857
Axis1:Block3 -2.407e-04 8.013e-03 3.457e+04 -0.030 0.97604
Axis2:Block3 5.460e-04 8.013e-03 3.457e+04 0.068 0.94568
Axis1:Block4 -4.620e-03 8.072e-03 3.457e+04 -0.572 0.56712
Axis2:Block4 -1.201e-02 8.072e-03 3.457e+04 -1.487 0.13692
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation matrix not shown by default, as p = 16 > 12.
Use print(summary(m), correlation=TRUE) or
vcov(summary(m)) if you need it
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Axis 488.58 244.289 2 34569 875.6926 < 2.2e-16 ***
Block 38.11 9.527 4 34619 34.1505 < 2.2e-16 ***
Accuracy 17.48 17.479 1 33291 62.6548 2.539e-15 ***
Axis:Block 3.79 0.473 8 34569 1.6972 0.09349 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Axis 1755.332 2 < 2.2e-16 ***
Block 136.602 4 < 2.2e-16 ***
Accuracy 62.655 1 2.463e-15 ***
Axis:Block 13.578 8 0.09345 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 144.003 1 < 2.2e-16 ***
Axis 1751.385 2 < 2.2e-16 ***
Block 136.602 4 < 2.2e-16 ***
Accuracy 62.655 1 2.463e-15 ***
Axis:Block 13.578 8 0.09345 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1NOTE: Results may be misleading due to involvement in interactions
--- EMMs by Axis (averaged over Blocks) ---
Axis emmean SE df asymp.LCL asymp.UCL
X 0.396 0.041 Inf 0.316 0.476
Y 0.414 0.041 Inf 0.334 0.494
Z 0.657 0.041 Inf 0.577 0.738
Results are averaged over the levels of: Block, Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) Axis comparisons (overall) ---
contrast estimate SE df z.ratio p.value
X - Y -0.0176 0.00698 Inf -2.524 0.0312
X - Z -0.2613 0.00698 Inf -37.439 <.0001
Y - Z -0.2436 0.00698 Inf -34.915 <.0001
Results are averaged over the levels of: Block, Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
--- EMMs by Axis within each Block ---
Block = 1:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.415 0.0424 Inf 0.332 0.498
Y 0.438 0.0424 Inf 0.355 0.521
Z 0.668 0.0424 Inf 0.585 0.751
Block = 2:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.414 0.0421 Inf 0.331 0.496
Y 0.440 0.0421 Inf 0.357 0.522
Z 0.698 0.0421 Inf 0.616 0.781
Block = 3:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.381 0.0421 Inf 0.299 0.464
Y 0.400 0.0421 Inf 0.317 0.482
Z 0.642 0.0421 Inf 0.560 0.725
Block = 4:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.418 0.0421 Inf 0.336 0.501
Y 0.429 0.0421 Inf 0.346 0.511
Z 0.701 0.0421 Inf 0.618 0.783
Block = 5:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.353 0.0419 Inf 0.271 0.435
Y 0.364 0.0419 Inf 0.281 0.446
Z 0.578 0.0419 Inf 0.496 0.660
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) Axis comparisons within each Block ---
Block = 1:
contrast estimate SE df z.ratio p.value
X - Y -0.0229 0.0167 Inf -1.365 0.3592
X - Z -0.2529 0.0167 Inf -15.110 <.0001
Y - Z -0.2301 0.0167 Inf -13.745 <.0001
Block = 2:
contrast estimate SE df z.ratio p.value
X - Y -0.0261 0.0156 Inf -1.673 0.2154
X - Z -0.2846 0.0156 Inf -18.282 <.0001
Y - Z -0.2586 0.0156 Inf -16.608 <.0001
Block = 3:
contrast estimate SE df z.ratio p.value
X - Y -0.0184 0.0155 Inf -1.188 0.4603
X - Z -0.2612 0.0155 Inf -16.865 <.0001
Y - Z -0.2428 0.0155 Inf -15.677 <.0001
Block = 4:
contrast estimate SE df z.ratio p.value
X - Y -0.0102 0.0156 Inf -0.654 0.7901
X - Z -0.2825 0.0156 Inf -18.063 <.0001
Y - Z -0.2723 0.0156 Inf -17.410 <.0001
Block = 5:
contrast estimate SE df z.ratio p.value
X - Y -0.0105 0.0145 Inf -0.726 0.7480
X - Z -0.2250 0.0145 Inf -15.516 <.0001
Y - Z -0.2145 0.0145 Inf -14.790 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates # 2) Within each phase (to match your within-phase reporting elsewhere)
for (ph in c("Preparation","Execution")) {
df_ph <- axes_long %>% filter(phase == ph) %>% droplevels()
if (nrow(df_ph) > 0) analyze_axes_vs_blocks(df_ph, label = paste("PHASE:", ph))
}
==============================
AXES × BLOCKS — PHASE: Preparation
==============================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Axis * Block + Accuracy + (1 | subject) + (1 | Trial)
Data: df
REML criterion at convergence: 2758.8
Scaled residuals:
Min 1Q Median 3Q Max
-2.0492 -0.3806 -0.1162 0.1486 21.5763
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.011441 0.10696
subject (Intercept) 0.001264 0.03556
Residual 0.067024 0.25889
Number of obs: 17613, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 1.372e-01 1.769e-02 6.214e+01 7.755 1.04e-10 ***
Axis1 -1.253e-02 2.768e-03 1.753e+04 -4.526 6.05e-06 ***
Axis2 -1.094e-02 2.768e-03 1.753e+04 -3.952 7.78e-05 ***
Block1 -7.772e-02 4.180e-03 1.754e+04 -18.595 < 2e-16 ***
Block2 4.705e-03 3.926e-03 1.755e+04 1.198 0.230754
Block3 7.096e-02 3.956e-03 1.755e+04 17.934 < 2e-16 ***
Block4 2.978e-03 3.957e-03 1.754e+04 0.753 0.451728
Accuracy1 -7.036e-03 2.096e-03 1.751e+04 -3.356 0.000792 ***
Axis1:Block1 1.349e-02 5.798e-03 1.753e+04 2.326 0.020021 *
Axis2:Block1 1.144e-02 5.798e-03 1.753e+04 1.973 0.048547 *
Axis1:Block2 -6.818e-03 5.535e-03 1.753e+04 -1.232 0.218004
Axis2:Block2 -5.683e-04 5.535e-03 1.753e+04 -0.103 0.918224
Axis1:Block3 -1.523e-02 5.516e-03 1.753e+04 -2.762 0.005755 **
Axis2:Block3 -4.979e-03 5.516e-03 1.753e+04 -0.903 0.366649
Axis1:Block4 2.938e-03 5.560e-03 1.753e+04 0.528 0.597286
Axis2:Block4 -3.952e-03 5.560e-03 1.753e+04 -0.711 0.477288
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation matrix not shown by default, as p = 16 > 12.
Use print(summary(m), correlation=TRUE) or
vcov(summary(m)) if you need it
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Axis 4.825 2.4123 2 17533 35.9918 2.517e-16 ***
Block 34.989 8.7473 4 17545 130.5101 < 2.2e-16 ***
Accuracy 0.755 0.7550 1 17506 11.2649 0.0007915 ***
Axis:Block 1.959 0.2449 8 17533 3.6544 0.0002906 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Axis 75.547 2 < 2.2e-16 ***
Block 522.040 4 < 2.2e-16 ***
Accuracy 11.265 1 0.0007899 ***
Axis:Block 29.235 8 0.0002883 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 60.136 1 8.853e-15 ***
Axis 71.984 2 2.339e-16 ***
Block 522.040 4 < 2.2e-16 ***
Accuracy 11.265 1 0.0007899 ***
Axis:Block 29.235 8 0.0002883 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1NOTE: Results may be misleading due to involvement in interactions
--- EMMs by Axis (averaged over Blocks) ---
Axis emmean SE df asymp.LCL asymp.UCL
X 0.125 0.0179 Inf 0.0896 0.160
Y 0.126 0.0179 Inf 0.0912 0.161
Z 0.161 0.0179 Inf 0.1256 0.196
Results are averaged over the levels of: Block, Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) Axis comparisons (overall) ---
contrast estimate SE df z.ratio p.value
X - Y -0.00159 0.00479 Inf -0.331 0.9413
X - Z -0.03600 0.00479 Inf -7.508 <.0001
Y - Z -0.03441 0.00479 Inf -7.176 <.0001
Results are averaged over the levels of: Block, Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
--- EMMs by Axis within each Block ---
Block = 1:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.0604 0.0194 Inf 0.0225 0.0984
Y 0.0600 0.0194 Inf 0.0220 0.0979
Z 0.0580 0.0194 Inf 0.0201 0.0960
Block = 2:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.1226 0.0191 Inf 0.0850 0.1601
Y 0.1304 0.0191 Inf 0.0929 0.1679
Z 0.1728 0.0191 Inf 0.1352 0.2103
Block = 3:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.1804 0.0191 Inf 0.1429 0.2179
Y 0.1922 0.0191 Inf 0.1547 0.2298
Z 0.2518 0.0191 Inf 0.2143 0.2894
Block = 4:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.1306 0.0192 Inf 0.0930 0.1682
Y 0.1253 0.0192 Inf 0.0877 0.1629
Z 0.1647 0.0192 Inf 0.1271 0.2022
Block = 5:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.1294 0.0190 Inf 0.0922 0.1665
Y 0.1234 0.0190 Inf 0.0862 0.1606
Z 0.1561 0.0190 Inf 0.1189 0.1932
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) Axis comparisons within each Block ---
Block = 1:
contrast estimate SE df z.ratio p.value
X - Y 0.000461 0.0114 Inf 0.040 0.9991
X - Z 0.002415 0.0114 Inf 0.212 0.9755
Y - Z 0.001954 0.0114 Inf 0.172 0.9839
Block = 2:
contrast estimate SE df z.ratio p.value
X - Y -0.007839 0.0107 Inf -0.731 0.7448
X - Z -0.050202 0.0107 Inf -4.684 <.0001
Y - Z -0.042363 0.0107 Inf -3.953 0.0002
Block = 3:
contrast estimate SE df z.ratio p.value
X - Y -0.011842 0.0107 Inf -1.110 0.5078
X - Z -0.071442 0.0107 Inf -6.697 <.0001
Y - Z -0.059600 0.0107 Inf -5.587 <.0001
Block = 4:
contrast estimate SE df z.ratio p.value
X - Y 0.005300 0.0108 Inf 0.492 0.8753
X - Z -0.034073 0.0108 Inf -3.160 0.0045
Y - Z -0.039374 0.0108 Inf -3.652 0.0008
Block = 5:
contrast estimate SE df z.ratio p.value
X - Y 0.005976 0.0100 Inf 0.598 0.8214
X - Z -0.026682 0.0100 Inf -2.668 0.0209
Y - Z -0.032658 0.0100 Inf -3.265 0.0031
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
==============================
AXES × BLOCKS — PHASE: Execution
==============================
--- Model Summary (lmerTest; Satterthwaite t-tests) ---
Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: RMS ~ Axis * Block + Accuracy + (1 | subject) + (1 | Trial)
Data: df
REML criterion at convergence: 14946.6
Scaled residuals:
Min 1Q Median 3Q Max
-5.3930 -0.4971 -0.0242 0.4173 18.2710
Random effects:
Groups Name Variance Std.Dev.
Trial (Intercept) 0.008388 0.09159
subject (Intercept) 0.104887 0.32386
Residual 0.137640 0.37100
Number of obs: 17043, groups: Trial, 48; subject, 18
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 8.538e-01 7.753e-02 1.803e+01 11.012 1.94e-09 ***
Axis1 -1.764e-01 4.039e-03 1.695e+04 -43.663 < 2e-16 ***
Axis2 -1.421e-01 4.039e-03 1.695e+04 -35.176 < 2e-16 ***
Block1 1.373e-01 6.195e-03 1.697e+04 22.171 < 2e-16 ***
Block2 4.779e-02 5.708e-03 1.697e+04 8.372 < 2e-16 ***
Block3 -1.081e-01 5.755e-03 1.699e+04 -18.783 < 2e-16 ***
Block4 4.479e-02 5.739e-03 1.697e+04 7.803 6.38e-15 ***
Accuracy1 -3.904e-02 3.055e-03 1.701e+04 -12.778 < 2e-16 ***
Axis1:Block1 -1.574e-02 8.590e-03 1.695e+04 -1.833 0.0669 .
Axis2:Block1 -2.024e-03 8.590e-03 1.695e+04 -0.236 0.8137
Axis1:Block2 -1.378e-02 8.051e-03 1.695e+04 -1.712 0.0869 .
Axis2:Block2 -3.281e-03 8.051e-03 1.695e+04 -0.408 0.6836
Axis1:Block3 1.601e-02 8.017e-03 1.695e+04 1.997 0.0459 *
Axis2:Block3 6.858e-03 8.017e-03 1.695e+04 0.855 0.3923
Axis1:Block4 -1.116e-02 8.070e-03 1.695e+04 -1.383 0.1667
Axis2:Block4 -1.934e-02 8.070e-03 1.695e+04 -2.397 0.0166 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation matrix not shown by default, as p = 16 > 12.
Use print(summary(m), correlation=TRUE) or
vcov(summary(m)) if you need it
--- lmerTest ANOVA (F-tests; Satterthwaite) ---
Type III Analysis of Variance Table with Satterthwaite's method
Sum Sq Mean Sq NumDF DenDF F value Pr(>F)
Axis 858.81 429.40 2 16955 3119.7640 < 2.2e-16 ***
Block 155.50 38.87 4 16972 282.4317 < 2.2e-16 ***
Accuracy 22.47 22.47 1 17005 163.2750 < 2.2e-16 ***
Axis:Block 7.21 0.90 8 16955 6.5458 1.476e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type II Wald χ² (car::Anova) ---
Analysis of Deviance Table (Type II Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
Axis 6223.795 2 < 2.2e-16 ***
Block 1129.727 4 < 2.2e-16 ***
Accuracy 163.275 1 < 2.2e-16 ***
Axis:Block 52.367 8 1.43e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
--- Type III Wald χ² (car::Anova; sum contrasts) ---
Analysis of Deviance Table (Type III Wald chisquare tests)
Response: RMS
Chisq Df Pr(>Chisq)
(Intercept) 121.272 1 < 2.2e-16 ***
Axis 6239.528 2 < 2.2e-16 ***
Block 1129.727 4 < 2.2e-16 ***
Accuracy 163.275 1 < 2.2e-16 ***
Axis:Block 52.367 8 1.43e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1NOTE: Results may be misleading due to involvement in interactions
--- EMMs by Axis (averaged over Blocks) ---
Axis emmean SE df asymp.LCL asymp.UCL
X 0.677 0.0776 Inf 0.525 0.830
Y 0.712 0.0776 Inf 0.560 0.864
Z 1.172 0.0776 Inf 1.020 1.324
Results are averaged over the levels of: Block, Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) Axis comparisons (overall) ---
contrast estimate SE df z.ratio p.value
X - Y -0.0343 0.007 Inf -4.900 <.0001
X - Z -0.4948 0.007 Inf -70.726 <.0001
Y - Z -0.4605 0.007 Inf -65.826 <.0001
Results are averaged over the levels of: Block, Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates
--- EMMs by Axis within each Block ---
Block = 1:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.799 0.0784 Inf 0.645 0.953
Y 0.847 0.0784 Inf 0.693 1.001
Z 1.327 0.0784 Inf 1.174 1.481
Block = 2:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.711 0.0783 Inf 0.558 0.865
Y 0.756 0.0783 Inf 0.603 0.910
Z 1.237 0.0783 Inf 1.084 1.390
Block = 3:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.585 0.0783 Inf 0.432 0.739
Y 0.610 0.0783 Inf 0.457 0.764
Z 1.041 0.0783 Inf 0.888 1.195
Block = 4:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.711 0.0783 Inf 0.558 0.864
Y 0.737 0.0783 Inf 0.584 0.891
Z 1.248 0.0783 Inf 1.094 1.401
Block = 5:
Axis emmean SE df asymp.LCL asymp.UCL
X 0.580 0.0782 Inf 0.427 0.733
Y 0.608 0.0782 Inf 0.455 0.761
Z 1.008 0.0782 Inf 0.855 1.161
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
Confidence level used: 0.95
--- Pairwise (Tukey) Axis comparisons within each Block ---
Block = 1:
contrast estimate SE df z.ratio p.value
X - Y -0.0480 0.0170 Inf -2.832 0.0129
X - Z -0.5283 0.0170 Inf -31.165 <.0001
Y - Z -0.4803 0.0170 Inf -28.334 <.0001
Block = 2:
contrast estimate SE df z.ratio p.value
X - Y -0.0448 0.0156 Inf -2.875 0.0113
X - Z -0.5256 0.0156 Inf -33.752 <.0001
Y - Z -0.4809 0.0156 Inf -30.876 <.0001
Block = 3:
contrast estimate SE df z.ratio p.value
X - Y -0.0251 0.0155 Inf -1.623 0.2360
X - Z -0.4559 0.0155 Inf -29.442 <.0001
Y - Z -0.4308 0.0155 Inf -27.819 <.0001
Block = 4:
contrast estimate SE df z.ratio p.value
X - Y -0.0261 0.0156 Inf -1.671 0.2165
X - Z -0.5364 0.0156 Inf -34.339 <.0001
Y - Z -0.5103 0.0156 Inf -32.669 <.0001
Block = 5:
contrast estimate SE df z.ratio p.value
X - Y -0.0274 0.0145 Inf -1.891 0.1413
X - Z -0.4276 0.0145 Inf -29.523 <.0001
Y - Z -0.4003 0.0145 Inf -27.632 <.0001
Results are averaged over the levels of: Accuracy
Degrees-of-freedom method: asymptotic
P value adjustment: tukey method for comparing a family of 3 estimates