Code
cat('\014') # clean terminalCode
rm(list = ls()) # clean workspace
library(tidyverse)
library(afex)
library(emmeans)
# library(performance)Arousal Mood Induction Protocol 2024
Physiological signals anlysis
Code
xclude <- c('p13_HA') # male participant
my_dodge <- .3
theme_set(theme_minimal())
a_posteriori <- function(afex_aov, sig_level = .05) {
factors <- as.list(rownames(afex_aov$anova_table))
for (j in 1:length(factors)) {
if (grepl(':', factors[[j]])) {
factors[[j]] <- unlist(strsplit(factors[[j]], ':'))
}
}
p_values <- afex_aov$anova_table$`Pr(>F)`
for (i in 1:length(p_values)) {
if (p_values[i] <= sig_level) {
cat(rep('_', 60), '\n', sep = '')
print(emmeans(afex_aov, factors[[i]], contr = 'pairwise'))
}
}
}Code
study_group <- c('p04_LA', 'p05_LA', 'p06_HA', 'p14_LA')
hrv_df <- read_csv('../data/hrv_hrf_hra_rsa_rrv_neurokit2.csv', col_types = cols()) |>
filter(!(sbj %in% xclude)) |>
mutate(log10_HRV_RMSSD = log10(HRV_RMSSD),
log10_RRV_RMSSD = log10(RRV_RMSSD),
arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control'))|>
mutate_if(is.character, as.factor)
rhrv_df <- read_csv('../data/hrv_rhrv.csv', col_types = cols()) |>
filter(!(sbj %in% xclude)) |>
mutate(log10_rMSSD = log10(rMSSD),
arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control')) |>
mutate_if(is.character, as.factor)
ans_df <- read_csv('../data/average_ans_indexes.csv', col_types = cols()) |>
filter(!(sbj %in% xclude)) |>
mutate(arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control')) |>
mutate_if(is.character, as.factor)
ccoh_df <- read_csv('../data/ccoh_ave.csv', col_types = cols()) |>
filter(!(sbj %in% xclude)) |>
mutate(arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control')) |>
mutate_if(is.character, as.factor)
hr_aperiodic_df <- read_csv('../data/hr_aperiodic_params.csv', col_types = cols()) |>
mutate(sbj = str_sub(subj, end = -2)) |>
filter(!(sbj %in% xclude)) |>
mutate(block = paste0('block', substr(subj, nchar(subj), nchar(subj)))) |>
merge(hrv_df[c('sbj', 'block', 'arousal', 'starting')], by = c('sbj', 'block')) |>
mutate(arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control')) |>
mutate_if(is.character, as.factor)
rsp_aperiodic_df <- read_csv('../data/rsp_aperiodic_params.csv', col_types = cols()) |>
mutate(sbj = str_sub(subj, end = -2)) |>
filter(!(sbj %in% xclude)) |>
mutate(block = paste0('block', substr(subj, nchar(subj), nchar(subj)))) |>
merge(hrv_df[c('sbj', 'block', 'arousal', 'starting')], by = c('sbj', 'block')) |>
mutate(arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control')) |>
mutate_if(is.character, as.factor)
hr_pow_peaks_df <- read_csv('../data/hr_power_peaks.csv', col_types = cols()) |>
mutate(sbj = str_sub(subj, end = -2)) |>
filter(!(sbj %in% xclude)) |>
mutate(block = paste0('block', substr(subj, nchar(subj), nchar(subj)))) |>
merge(hrv_df[c('sbj', 'block', 'arousal', 'starting')], by = c('sbj', 'block')) |>
mutate(arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control')) |>
mutate_if(is.character, as.factor)
rsp_pow_peaks_df <- read_csv('../data/rsp_power_peaks.csv', col_types = cols()) |>
mutate(sbj = str_sub(subj, end = -2)) |>
filter(!(sbj %in% xclude)) |>
mutate(block = paste0('block', substr(subj, nchar(subj), nchar(subj)))) |>
merge(hrv_df[c('sbj', 'block', 'arousal', 'starting')], by = c('sbj', 'block')) |>
mutate(arousal = recode(arousal, 'HA' = 'high', 'LA' = 'low'),
group = if_else(sbj %in% study_group, 'study', 'control')) |>
mutate_if(is.character, as.factor)Summary
Code
ans_table <- xtabs(~ group + starting, data = unique(hrv_df[c('sbj', 'group', 'starting')]))
addmargins(ans_table, margin = c(1, 2)) starting
group HA LA Sum
control 4 2 6
study 1 3 4
Sum 5 5 10Code
summary(hrv_df) sbj starting block arousal heart_rate HRV_MeanNN
p01_HA : 4 HA:20 block1:10 high:20 Min. :53.36 Min. : 649.7
p02_LA : 4 LA:20 block2:10 low :20 1st Qu.:72.34 1st Qu.: 717.7
p03_HA : 4 block3:10 Median :77.62 Median : 773.1
p04_LA : 4 block4:10 Mean :76.31 Mean : 801.6
p05_LA : 4 3rd Qu.:83.60 3rd Qu.: 829.4
p06_HA : 4 Max. :92.36 Max. :1124.4
(Other):16
HRV_SDNN HRV_SDANN1 HRV_SDNNI1 HRV_RMSSD
Min. :23.62 Min. : 5.043 Min. :23.21 Min. : 13.52
1st Qu.:38.06 1st Qu.:10.461 1st Qu.:34.46 1st Qu.: 22.46
Median :61.41 Median :13.685 Median :59.04 Median : 34.97
Mean :56.12 Mean :17.634 Mean :53.03 Mean : 38.98
3rd Qu.:67.85 3rd Qu.:25.489 3rd Qu.:66.03 3rd Qu.: 46.47
Max. :95.02 Max. :42.214 Max. :94.48 Max. :105.41
HRV_SDSD HRV_CVNN HRV_CVSD HRV_MedianNN
Min. : 13.54 Min. :0.03099 Min. :0.01958 Min. : 650.0
1st Qu.: 22.48 1st Qu.:0.05342 1st Qu.:0.03148 1st Qu.: 715.5
Median : 35.01 Median :0.06925 Median :0.04581 Median : 770.5
Mean : 39.04 Mean :0.06938 Mean :0.04709 Mean : 799.5
3rd Qu.: 46.54 3rd Qu.:0.08746 3rd Qu.:0.05382 3rd Qu.: 824.4
Max. :105.56 Max. :0.11158 Max. :0.11776 Max. :1129.5
HRV_MadNN HRV_MCVNN HRV_IQRNN HRV_SDRMSSD
Min. : 23.72 Min. :0.03308 Min. : 31.00 Min. :0.9015
1st Qu.: 36.14 1st Qu.:0.04958 1st Qu.: 49.38 1st Qu.:1.2234
Median : 65.61 Median :0.06829 Median : 88.12 Median :1.4443
Mean : 59.06 Mean :0.07355 Mean : 80.59 Mean :1.5638
3rd Qu.: 77.47 3rd Qu.:0.09576 3rd Qu.:108.31 3rd Qu.:1.9651
Max. :109.71 Max. :0.12605 Max. :160.00 Max. :2.2278
HRV_Prc20NN HRV_Prc80NN HRV_pNN50 HRV_pNN20
Min. : 625.0 Min. : 673.0 Min. : 0.000 Min. :12.27
1st Qu.: 676.5 1st Qu.: 773.0 1st Qu.: 1.945 1st Qu.:38.82
Median : 731.2 Median : 820.0 Median :13.624 Median :57.99
Mean : 752.8 Mean : 851.3 Mean :19.406 Mean :52.86
3rd Qu.: 760.3 3rd Qu.: 907.5 3rd Qu.:30.008 3rd Qu.:70.68
Max. :1064.0 Max. :1195.0 Max. :67.761 Max. :86.87
HRV_MinNN HRV_MaxNN HRV_HTI HRV_TINN
Min. :523.0 Min. : 738.0 Min. : 6.871 Min. : 54.69
1st Qu.:591.8 1st Qu.: 837.5 1st Qu.: 9.891 1st Qu.:132.81
Median :634.5 Median : 940.5 Median :14.614 Median :167.97
Mean :655.4 Mean : 950.9 Mean :13.847 Mean :175.00
3rd Qu.:683.5 3rd Qu.:1011.8 3rd Qu.:16.802 3rd Qu.:234.38
Max. :868.0 Max. :1321.0 Max. :21.294 Max. :320.31
HRV_VLF HRV_LF HRV_HF HRV_VHF
Min. :0.0005632 Min. :0.004142 Min. :0.001650 Min. :4.116e-05
1st Qu.:0.0048864 1st Qu.:0.012272 1st Qu.:0.004969 1st Qu.:1.564e-04
Median :0.0099804 Median :0.017878 Median :0.011713 Median :3.234e-04
Mean :0.0093022 Mean :0.020077 Mean :0.015619 Mean :4.024e-04
3rd Qu.:0.0139517 3rd Qu.:0.025172 3rd Qu.:0.024310 3rd Qu.:5.483e-04
Max. :0.0204093 Max. :0.049360 Max. :0.044648 Max. :1.665e-03
HRV_TP HRV_LFHF HRV_LFn HRV_HFn
Min. :0.01502 Min. : 0.1452 Min. :0.1233 Min. :0.0634
1st Qu.:0.03356 1st Qu.: 0.5590 1st Qu.:0.2815 1st Qu.:0.1552
Median :0.04211 Median : 1.6526 Median :0.4211 Median :0.2928
Mean :0.04540 Mean : 2.9930 Mean :0.4710 Mean :0.3135
3rd Qu.:0.05872 3rd Qu.: 4.1354 3rd Qu.:0.6115 3rd Qu.:0.4635
Max. :0.08247 Max. :13.6533 Max. :0.8657 Max. :0.8489
HRV_LnHF HRV_SD1 HRV_SD2 HRV_SD1SD2
Min. :-6.407 Min. : 9.573 Min. : 28.98 Min. :0.2307
1st Qu.:-5.305 1st Qu.:15.899 1st Qu.: 51.55 1st Qu.:0.2635
Median :-4.447 Median :24.756 Median : 78.85 Median :0.3695
Mean :-4.532 Mean :27.602 Mean : 74.02 Mean :0.3667
3rd Qu.:-3.717 3rd Qu.:32.907 3rd Qu.: 91.05 3rd Qu.:0.4479
Max. :-3.109 Max. :74.645 Max. :118.74 Max. :0.6669
HRV_S HRV_CSI HRV_CVI HRV_CSI_Modified
Min. : 1051 Min. :1.499 Min. :3.729 Min. : 209.8
1st Qu.: 2256 1st Qu.:2.233 1st Qu.:4.060 1st Qu.: 623.4
Median : 6518 Median :2.706 Median :4.521 Median : 811.0
Mean : 7323 Mean :2.946 Mean :4.429 Mean : 858.2
3rd Qu.: 8795 3rd Qu.:3.796 3rd Qu.:4.651 3rd Qu.:1083.8
Max. :26248 Max. :4.334 Max. :5.126 Max. :1570.0
HRF_PIP HRF_IALS HRF_PSS HRF_PAS
Min. :0.2038 Min. :0.1971 Min. :0.1765 Min. :0.000000
1st Qu.:0.3583 1st Qu.:0.3549 1st Qu.:0.4278 1st Qu.:0.007568
Median :0.4008 Median :0.4014 Median :0.5233 Median :0.015512
Mean :0.3985 Mean :0.3948 Mean :0.5227 Mean :0.035453
3rd Qu.:0.4502 3rd Qu.:0.4463 3rd Qu.:0.6747 3rd Qu.:0.037655
Max. :0.6581 Max. :0.6592 Max. :0.9432 Max. :0.175676
HRA_GI HRA_SI HRA_AI HRA_PI
Min. :49.17 Min. :49.16 Min. :49.16 Min. :39.65
1st Qu.:49.61 1st Qu.:49.63 1st Qu.:49.64 1st Qu.:45.55
Median :49.91 Median :49.92 Median :49.89 Median :47.98
Mean :49.92 Mean :49.93 Mean :49.92 Mean :48.06
3rd Qu.:50.16 3rd Qu.:50.15 3rd Qu.:50.17 3rd Qu.:49.95
Max. :50.71 Max. :50.75 Max. :50.73 Max. :61.45
HRA_C1d HRA_C1a HRA_SD1d HRA_SD1a
Min. :0.4012 Min. :0.3613 Min. : 6.451 Min. : 6.638
1st Qu.:0.4483 1st Qu.:0.4876 1st Qu.:10.719 1st Qu.:12.156
Median :0.4826 Median :0.5174 Median :18.296 Median :16.766
Mean :0.4875 Mean :0.5125 Mean :19.180 Mean :19.788
3rd Qu.:0.5124 3rd Qu.:0.5517 3rd Qu.:21.793 3rd Qu.:25.450
Max. :0.6387 Max. :0.5988 Max. :52.238 Max. :53.321
HRA_C2d HRA_C2a HRA_SD2d HRA_SD2a
Min. :0.4056 Min. :0.3762 Min. :22.87 Min. :17.80
1st Qu.:0.4725 1st Qu.:0.4644 1st Qu.:35.61 1st Qu.:36.55
Median :0.4978 Median :0.5022 Median :56.86 Median :53.78
Mean :0.5075 Mean :0.4925 Mean :52.25 Mean :52.28
3rd Qu.:0.5356 3rd Qu.:0.5275 3rd Qu.:63.55 3rd Qu.:67.03
Max. :0.6238 Max. :0.5944 Max. :83.93 Max. :84.00
HRA_Cd HRA_Ca HRA_SDNNd HRA_SDNNa
Min. :0.4183 Min. :0.4198 Min. :17.75 Min. :15.27
1st Qu.:0.4718 1st Qu.:0.4730 1st Qu.:26.05 1st Qu.:27.71
Median :0.4967 Median :0.5033 Median :42.52 Median :41.79
Mean :0.5013 Mean :0.4987 Mean :39.48 Mean :39.79
3rd Qu.:0.5270 3rd Qu.:0.5282 3rd Qu.:47.41 3rd Qu.:49.95
Max. :0.5802 Max. :0.5817 Max. :68.03 Max. :66.50
HRV_DFA_alpha1 HRV_MFDFA_alpha1_Width HRV_MFDFA_alpha1_Peak
Min. :0.6120 Min. :0.634 Min. :0.820
1st Qu.:0.9498 1st Qu.:1.352 1st Qu.:1.073
Median :1.1976 Median :1.874 Median :1.387
Mean :1.2164 Mean :1.866 Mean :1.401
3rd Qu.:1.4840 3rd Qu.:2.362 3rd Qu.:1.664
Max. :1.7196 Max. :3.538 Max. :2.135
HRV_MFDFA_alpha1_Mean HRV_MFDFA_alpha1_Max HRV_MFDFA_alpha1_Delta
Min. :1.166 Min. :-3.4247 Min. :-4.4032
1st Qu.:1.636 1st Qu.:-2.4354 1st Qu.:-3.0365
Median :2.058 Median :-1.2936 Median :-2.0737
Mean :2.000 Mean :-1.4954 Mean :-2.1333
3rd Qu.:2.291 3rd Qu.:-0.4391 3rd Qu.:-1.1040
Max. :3.009 Max. : 0.5512 Max. :-0.2557
HRV_MFDFA_alpha1_Asymmetry HRV_MFDFA_alpha1_Fluctuation
Min. :-0.427751 Min. :0.0001604
1st Qu.:-0.266249 1st Qu.:0.0008625
Median :-0.170848 Median :0.0018421
Mean :-0.186395 Mean :0.0031072
3rd Qu.:-0.122207 3rd Qu.:0.0046781
Max. :-0.007863 Max. :0.0115272
HRV_MFDFA_alpha1_Increment HRV_DFA_alpha2 HRV_MFDFA_alpha2_Width
Min. :0.02981 Min. :0.2191 Min. :0.07798
1st Qu.:0.13907 1st Qu.:0.5939 1st Qu.:0.33904
Median :0.25851 Median :0.8427 Median :0.48868
Mean :0.33281 Mean :0.7602 Mean :0.53592
3rd Qu.:0.48019 3rd Qu.:0.9764 3rd Qu.:0.70801
Max. :1.09117 Max. :1.2028 Max. :1.24970
HRV_MFDFA_alpha2_Peak HRV_MFDFA_alpha2_Mean HRV_MFDFA_alpha2_Max
Min. :0.2487 Min. :0.2124 Min. :-1.1453
1st Qu.:0.5022 1st Qu.:0.7044 1st Qu.: 0.2097
Median :0.7506 Median :0.8406 Median : 0.5350
Mean :0.7576 Mean :0.8224 Mean : 0.4891
3rd Qu.:1.0047 3rd Qu.:0.9691 3rd Qu.: 1.0027
Max. :1.1199 Max. :1.2930 Max. : 1.5751
HRV_MFDFA_alpha2_Delta HRV_MFDFA_alpha2_Asymmetry HRV_MFDFA_alpha2_Fluctuation
Min. :-1.8613 Min. :-1.0000 Min. :1.040e-06
1st Qu.:-0.5147 1st Qu.:-0.5767 1st Qu.:3.386e-05
Median :-0.1729 Median :-0.3569 Median :7.472e-05
Mean :-0.2918 Mean :-0.3992 Mean :1.480e-04
3rd Qu.: 0.2000 3rd Qu.:-0.1242 3rd Qu.:2.038e-04
Max. : 0.7492 Max. : 0.0000 Max. :6.746e-04
HRV_MFDFA_alpha2_Increment HRV_ApEn HRV_SampEn HRV_ShanEn
Min. :0.000633 Min. :0.7589 Min. :0.7803 Min. :6.319
1st Qu.:0.007493 1st Qu.:1.0083 1st Qu.:1.2358 1st Qu.:6.882
Median :0.017048 Median :1.0932 Median :1.4043 Median :7.236
Mean :0.022527 Mean :1.0625 Mean :1.3901 Mean :7.116
3rd Qu.:0.033356 3rd Qu.:1.1398 3rd Qu.:1.5426 3rd Qu.:7.379
Max. :0.079039 Max. :1.2316 Max. :2.0716 Max. :7.603
HRV_FuzzyEn HRV_MSEn HRV_CMSEn HRV_RCMSEn
Min. :0.7513 Min. :0.8365 Min. :1.230 Min. :1.753
1st Qu.:0.9671 1st Qu.:1.3322 1st Qu.:1.339 1st Qu.:1.988
Median :1.1443 Median :1.4288 Median :1.362 Median :2.081
Mean :1.1027 Mean :1.4077 Mean :1.358 Mean :2.076
3rd Qu.:1.2565 3rd Qu.:1.5248 3rd Qu.:1.387 3rd Qu.:2.187
Max. :1.4632 Max. :1.6822 Max. :1.464 Max. :2.320
HRV_CD HRV_HFD HRV_KFD HRV_LZC
Min. :1.347 Min. :1.424 Min. :2.413 Min. :0.5218
1st Qu.:1.666 1st Qu.:1.626 1st Qu.:2.734 1st Qu.:0.7006
Median :1.744 Median :1.806 Median :2.967 Median :0.7837
Mean :1.725 Mean :1.744 Mean :3.127 Mean :0.7773
3rd Qu.:1.791 3rd Qu.:1.892 3rd Qu.:3.364 3rd Qu.:0.8572
Max. :1.895 Max. :2.041 Max. :4.983 Max. :0.9932
RSA_P2T_Mean RSA_P2T_Mean_log RSA_P2T_SD RSA_P2T_NoRSA
Min. : 25.33 Min. :3.232 Min. :12.94 Min. : 0.0
1st Qu.: 45.69 1st Qu.:3.822 1st Qu.:30.43 1st Qu.: 0.0
Median : 65.85 Median :4.184 Median :41.35 Median : 0.0
Mean : 86.85 Mean :4.287 Mean :41.58 Mean : 1.1
3rd Qu.:131.45 3rd Qu.:4.879 3rd Qu.:51.70 3rd Qu.: 0.0
Max. :219.22 Max. :5.390 Max. :81.39 Max. :14.0
RSA_PorgesBohrer RSA_Gates_Mean RSA_Gates_Mean_log RSA_Gates_SD
Min. :-6.583 Min. :7.433 Min. :2.006 Min. :0.04312
1st Qu.:-5.813 1st Qu.:7.731 1st Qu.:2.045 1st Qu.:0.10268
Median :-5.051 Median :7.924 Median :2.070 Median :0.13116
Mean :-5.202 Mean :7.983 Mean :2.076 Mean :0.14402
3rd Qu.:-4.614 3rd Qu.:8.191 3rd Qu.:2.103 3rd Qu.:0.19296
Max. :-2.963 Max. :8.783 Max. :2.173 Max. :0.26885
rsp_rate RRV_RMSSD RRV_MeanBB RRV_SDBB
Min. : 5.965 Min. : 558.7 Min. : 2946 Min. : 466.1
1st Qu.:12.078 1st Qu.: 968.7 1st Qu.: 3812 1st Qu.: 720.5
Median :14.614 Median :1302.3 Median : 4106 Median : 995.1
Mean :13.721 Mean :1501.0 Mean : 4887 Mean :1148.6
3rd Qu.:15.740 3rd Qu.:1687.6 3rd Qu.: 4972 3rd Qu.:1460.9
Max. :20.366 Max. :4168.8 Max. :10059 Max. :2535.2
RRV_SDSD RRV_CVBB RRV_CVSD RRV_MedianBB
Min. : 562.5 Min. :0.1192 Min. :0.1206 Min. :2819
1st Qu.: 975.4 1st Qu.:0.1888 1st Qu.:0.2431 1st Qu.:3664
Median :1313.1 Median :0.2397 Median :0.3031 Median :3904
Mean :1516.6 Mean :0.2300 Mean :0.2968 Mean :4746
3rd Qu.:1701.3 3rd Qu.:0.2622 3rd Qu.:0.3585 3rd Qu.:4705
Max. :4242.0 Max. :0.3823 Max. :0.4827 Max. :9789
RRV_MadBB RRV_MCVBB RRV_VLF RRV_LF
Min. : 358.8 Min. :0.08535 Min. :0.004080 Min. :0.001397
1st Qu.: 493.1 1st Qu.:0.12866 1st Qu.:0.008827 1st Qu.:0.008026
Median : 657.2 Median :0.18584 Median :0.012042 Median :0.011014
Mean : 979.0 Mean :0.18826 Mean :0.011931 Mean :0.014982
3rd Qu.:1035.6 3rd Qu.:0.22358 3rd Qu.:0.014926 3rd Qu.:0.021209
Max. :3282.5 Max. :0.41311 Max. :0.020489 Max. :0.044389
RRV_HF RRV_LFHF RRV_LFn RRV_HFn
Min. :2.241e-06 Min. : 5.865 Min. :0.1928 Min. :9.865e-05
1st Qu.:1.054e-04 1st Qu.: 14.741 1st Qu.:0.3759 1st Qu.:5.716e-03
Median :3.693e-04 Median : 31.937 Median :0.5004 Median :1.753e-02
Mean :8.108e-04 Mean : 248.988 Mean :0.4973 Mean :2.324e-02
3rd Qu.:1.373e-03 3rd Qu.: 63.052 3rd Qu.:0.6092 3rd Qu.:3.324e-02
Max. :4.004e-03 Max. :3637.081 Max. :0.8457 Max. :1.032e-01
RRV_SD1 RRV_SD2 RRV_SD2SD1 RRV_ApEn
Min. : 397.7 Min. : 463.3 Min. :0.5309 Min. :0.09514
1st Qu.: 689.7 1st Qu.: 743.4 1st Qu.:1.0126 1st Qu.:0.47566
Median : 928.5 Median :1010.7 Median :1.1850 Median :0.56197
Mean :1072.4 Mean :1193.9 Mean :1.1817 Mean :0.53443
3rd Qu.:1203.0 3rd Qu.:1472.3 3rd Qu.:1.2901 3rd Qu.:0.66925
Max. :2999.5 Max. :3154.2 Max. :1.8824 Max. :0.84394
RRV_SampEn RRV_DFA_alpha2 RRV_MFDFA_alpha2_Width RRV_MFDFA_alpha2_Peak
Min. :0.6931 Min. :0.2261 Min. :0.2969 Min. :0.2914
1st Qu.:1.5519 1st Qu.:0.5014 1st Qu.:0.5044 1st Qu.:0.5963
Median :1.7533 Median :0.5776 Median :0.7488 Median :0.7027
Mean : Inf Mean :0.6157 Mean :0.8157 Mean :0.7654
3rd Qu.:2.1449 3rd Qu.:0.7789 3rd Qu.:1.0059 3rd Qu.:0.9821
Max. : Inf Max. :1.0220 Max. :1.8727 Max. :1.3448
NA's :14 NA's :14 NA's :14
RRV_MFDFA_alpha2_Mean RRV_MFDFA_alpha2_Max RRV_MFDFA_alpha2_Delta
Min. :0.2366 Min. :-0.2278 Min. :-0.70089
1st Qu.:0.5670 1st Qu.: 0.2128 1st Qu.:-0.17799
Median :0.7528 Median : 0.3472 Median : 0.12867
Mean :0.7546 Mean : 0.3660 Mean : 0.04354
3rd Qu.:0.9189 3rd Qu.: 0.5596 3rd Qu.: 0.22658
Max. :1.2787 Max. : 0.7456 Max. : 0.62625
NA's :14 NA's :14 NA's :14
RRV_MFDFA_alpha2_Asymmetry RRV_MFDFA_alpha2_Fluctuation
Min. :-0.6719 Min. :0.0000004
1st Qu.:-0.5869 1st Qu.:0.0000097
Median :-0.5282 Median :0.0000526
Mean :-0.5119 Mean :0.0002140
3rd Qu.:-0.4298 3rd Qu.:0.0002116
Max. :-0.3385 Max. :0.0025105
NA's :14 NA's :14
RRV_MFDFA_alpha2_Increment log10_HRV_RMSSD log10_RRV_RMSSD group
Min. :0.003212 Min. :1.131 Min. :2.747 control:24
1st Qu.:0.010450 1st Qu.:1.351 1st Qu.:2.986 study :16
Median :0.027182 Median :1.544 Median :3.114
Mean :0.048626 Mean :1.536 Mean :3.116
3rd Qu.:0.063279 3rd Qu.:1.667 3rd Qu.:3.226
Max. :0.306067 Max. :2.023 Max. :3.620
NA's :14 Time Domain Heart Rate Variability (HRV)
Heart Rate
Code
heart_rate_anova <- aov_ez('sbj',
'heart_rate', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
heart_rate_afex_plot <-
afex_plot(
heart_rate_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(heart_rate_afex_plot))
Code
print(heart_rate_anova)Anova Table (Type 3 tests)
Response: heart_rate
Effect df MSE F ges p.value
1 group 1, 6 307.42 0.00 <.001 .957
2 starting 1, 6 307.42 0.12 .019 .742
3 group:starting 1, 6 307.42 0.02 .003 .897
4 arousal 1, 6 0.34 5.89 + .001 .051
5 group:arousal 1, 6 0.34 13.67 * .003 .010
6 starting:arousal 1, 6 0.34 21.83 ** .004 .003
7 group:starting:arousal 1, 6 0.34 1.15 <.001 .324
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(heart_rate_anova)____________________________________________________________
$emmeans
group arousal emmean SE df lower.CL upper.CL
control high 76.9 5.44 6 63.6 90.3
study high 75.3 7.25 6 57.6 93.1
control low 76.6 5.31 6 63.6 89.6
study low 77.2 7.07 6 59.9 94.5
Results are averaged over the levels of: starting
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control high - study high 1.613 9.060 6 0.178 0.9978
control high - control low 0.379 0.358 6 1.059 0.7246
control high - study low -0.216 8.920 6 -0.024 1.0000
study high - control low -1.233 8.980 6 -0.137 0.9990
study high - study low -1.829 0.478 6 -3.827 0.0330
control low - study low -0.596 8.840 6 -0.067 0.9999
Results are averaged over the levels of: starting
P value adjustment: tukey method for comparing a family of 4 estimates
____________________________________________________________
$emmeans
starting arousal emmean SE df lower.CL upper.CL
HA high 77.0 7.02 6 59.8 94.2
LA high 75.3 5.73 6 61.3 89.3
HA low 79.1 6.85 6 62.3 95.9
LA low 74.6 5.59 6 60.9 88.3
Results are averaged over the levels of: group
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
HA high - LA high 1.690 9.060 6 0.187 0.9974
HA high - HA low -2.120 0.463 6 -4.582 0.0148
HA high - LA low 2.361 8.970 6 0.263 0.9930
LA high - HA low -3.810 8.930 6 -0.427 0.9717
LA high - LA low 0.671 0.378 6 1.775 0.3678
HA low - LA low 4.481 8.840 6 0.507 0.9545
Results are averaged over the levels of: group
P value adjustment: tukey method for comparing a family of 4 estimates HRV_SDNN
Code
sdnn_anova <- aov_ez('sbj',
'HRV_SDNN', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
sdnn_afex_plot <-
afex_plot(
sdnn_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(sdnn_afex_plot))
Code
print(sdnn_anova)Anova Table (Type 3 tests)
Response: HRV_SDNN
Effect df MSE F ges p.value
1 group 1, 6 1181.21 0.08 .013 .789
2 starting 1, 6 1181.21 0.29 .046 .608
3 group:starting 1, 6 1181.21 0.00 <.001 .978
4 arousal 1, 6 18.74 0.07 <.001 .800
5 group:arousal 1, 6 18.74 0.80 .002 .406
6 starting:arousal 1, 6 18.74 0.96 .002 .365
7 group:starting:arousal 1, 6 18.74 2.36 .006 .175
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(sdnn_anova)HRV_CVNN
Code
cvnn_anova <- aov_ez('sbj',
'HRV_CVNN', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
cvnn_afex_plot <-
afex_plot(
cvnn_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(cvnn_afex_plot))
Code
print(cvnn_anova)Anova Table (Type 3 tests)
Response: HRV_CVNN
Effect df MSE F ges p.value
1 group 1, 6 0.00 0.17 .028 .692
2 starting 1, 6 0.00 0.22 .035 .653
3 group:starting 1, 6 0.00 0.03 .006 .858
4 arousal 1, 6 0.00 0.00 <.001 .998
5 group:arousal 1, 6 0.00 0.56 .002 .481
6 starting:arousal 1, 6 0.00 0.46 .001 .524
7 group:starting:arousal 1, 6 0.00 4.18 + .011 .087
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(cvnn_anova)log10_HRV_RMSSD
Code
rmssd_anova <- aov_ez('sbj',
'log10_HRV_RMSSD', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
rmssd_afex_plot <-
afex_plot(
rmssd_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rmssd_afex_plot))
Code
print(rmssd_anova)Anova Table (Type 3 tests)
Response: log10_HRV_RMSSD
Effect df MSE F ges p.value
1 group 1, 6 0.15 0.00 <.001 .965
2 starting 1, 6 0.15 0.02 .004 .886
3 group:starting 1, 6 0.15 0.07 .011 .803
4 arousal 1, 6 0.00 0.20 <.001 .672
5 group:arousal 1, 6 0.00 0.69 .001 .439
6 starting:arousal 1, 6 0.00 2.84 .005 .143
7 group:starting:arousal 1, 6 0.00 0.09 <.001 .770
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rmssd_anova)
# check_autocorrelation(rmssd_anova)
# check_heteroscedasticity(rmssd_anova)
# plot(check_collinearity(rmssd_anova))
# normy <- check_normality(rmssd_anova)
# plot(normy, type = 'density')
# plot(normy, type = 'qq')HRV_IQRNN
Code
iqrnn_anova <- aov_ez('sbj',
'HRV_IQRNN', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
iqrnn_afex_plot <-
afex_plot(
iqrnn_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(iqrnn_afex_plot))
Code
print(iqrnn_anova)Anova Table (Type 3 tests)
Response: HRV_IQRNN
Effect df MSE F ges p.value
1 group 1, 6 2924.57 0.47 .071 .518
2 starting 1, 6 2924.57 0.41 .062 .545
3 group:starting 1, 6 2924.57 0.04 .006 .852
4 arousal 1, 6 101.22 0.41 .002 .545
5 group:arousal 1, 6 101.22 1.08 .006 .339
6 starting:arousal 1, 6 101.22 2.40 .013 .172
7 group:starting:arousal 1, 6 101.22 0.74 .004 .422
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(iqrnn_anova)HRV_HTI
Code
hti_anova <- aov_ez('sbj',
'HRV_HTI', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
hti_afex_plot <-
afex_plot(
hti_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hti_afex_plot))
Code
print(hti_anova)Anova Table (Type 3 tests)
Response: HRV_HTI
Effect df MSE F ges p.value
1 group 1, 6 46.12 0.11 .018 .750
2 starting 1, 6 46.12 0.34 .053 .581
3 group:starting 1, 6 46.12 0.12 .019 .745
4 arousal 1, 6 0.13 26.21 ** .012 .002
5 group:arousal 1, 6 0.13 88.10 *** .040 <.001
6 starting:arousal 1, 6 0.13 51.86 *** .024 <.001
7 group:starting:arousal 1, 6 0.13 66.53 *** .031 <.001
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(hti_anova)____________________________________________________________
$emmeans
arousal emmean SE df lower.CL upper.CL
high 14.4 1.71 6 10.27 18.6
low 13.5 1.76 6 9.18 17.8
Results are averaged over the levels of: group, starting
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
high - low 0.947 0.185 6 5.120 0.0022
Results are averaged over the levels of: group, starting
____________________________________________________________
$emmeans
group arousal emmean SE df lower.CL upper.CL
control high 14.2 2.05 6 9.14 19.2
study high 14.7 2.73 6 8.05 21.4
control low 14.9 2.12 6 9.76 20.1
study low 12.0 2.82 6 5.14 19.0
Results are averaged over the levels of: starting
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control high - study high -0.580 3.410 6 -0.170 0.9981
control high - control low -0.789 0.222 6 -3.555 0.0449
control high - study low 2.102 3.490 6 0.603 0.9275
study high - control low -0.209 3.450 6 -0.060 0.9999
study high - study low 2.682 0.296 6 9.066 0.0004
control low - study low 2.891 3.530 6 0.820 0.8436
Results are averaged over the levels of: starting
P value adjustment: tukey method for comparing a family of 4 estimates
____________________________________________________________
$emmeans
starting arousal emmean SE df lower.CL upper.CL
HA high 14.1 2.64 6 7.63 20.6
LA high 14.8 2.16 6 9.50 20.1
HA low 11.8 2.73 6 5.13 18.5
LA low 15.2 2.23 6 9.71 20.6
Results are averaged over the levels of: group
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
HA high - LA high -0.688 3.410 6 -0.202 0.9968
HA high - HA low 2.278 0.286 6 7.954 0.0009
HA high - LA low -1.073 3.460 6 -0.310 0.9886
LA high - HA low 2.967 3.480 6 0.852 0.8287
LA high - LA low -0.385 0.234 6 -1.646 0.4232
HA low - LA low -3.351 3.530 6 -0.950 0.7809
Results are averaged over the levels of: group
P value adjustment: tukey method for comparing a family of 4 estimates
____________________________________________________________
$emmeans
group starting arousal emmean SE df lower.CL upper.CL
control HA high 12.5 2.36 6 6.68 18.2
study HA high 15.7 4.73 6 4.16 27.3
control LA high 15.8 3.34 6 7.66 24.0
study LA high 13.7 2.73 6 7.05 20.4
control HA low 13.4 2.44 6 7.45 19.4
study HA low 10.2 4.89 6 -1.75 22.2
control LA low 16.5 3.46 6 8.00 24.9
study LA low 13.9 2.82 6 6.98 20.8
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control HA high - study HA high -3.271 5.290 6 -0.619 0.9969
control HA high - control LA high -3.379 4.100 6 -0.825 0.9841
control HA high - study LA high -1.269 3.610 6 -0.351 0.9999
control HA high - control HA low -0.965 0.256 6 -3.768 0.0888
control HA high - study HA low 2.251 5.430 6 0.415 0.9997
control HA high - control LA low -3.991 4.190 6 -0.953 0.9667
control HA high - study LA low -1.426 3.680 6 -0.387 0.9998
study HA high - control LA high -0.108 5.790 6 -0.019 1.0000
study HA high - study LA high 2.002 5.460 6 0.367 0.9999
study HA high - control HA low 2.305 5.320 6 0.433 0.9997
study HA high - study HA low 5.522 0.512 6 10.776 0.0005
study HA high - control LA low -0.720 5.860 6 -0.123 1.0000
study HA high - study LA low 1.845 5.510 6 0.335 0.9999
control LA high - study LA high 2.110 4.320 6 0.489 0.9993
control LA high - control HA low 2.413 4.140 6 0.583 0.9978
control LA high - study HA low 5.630 5.920 6 0.951 0.9671
control LA high - control LA low -0.612 0.362 6 -1.690 0.6961
control LA high - study LA low 1.953 4.380 6 0.446 0.9996
study LA high - control HA low 0.303 3.660 6 0.083 1.0000
study LA high - study HA low 3.520 5.600 6 0.629 0.9966
study LA high - control LA low -2.723 4.400 6 -0.618 0.9969
study LA high - study LA low -0.158 0.296 6 -0.532 0.9987
control HA low - study HA low 3.217 5.460 6 0.589 0.9977
control HA low - control LA low -3.026 4.230 6 -0.715 0.9927
control HA low - study LA low -0.461 3.730 6 -0.123 1.0000
study HA low - control LA low -6.242 5.990 6 -1.043 0.9490
study HA low - study LA low -3.677 5.640 6 -0.652 0.9957
control LA low - study LA low 2.565 4.460 6 0.575 0.9980
P value adjustment: tukey method for comparing a family of 8 estimates Autonomic Nervous System Indexes (Candia-Rivera et al, 2023; Valenza et al, 2018)
CSI_ave
3 middle minutes in each block to avoid block transitions
Code
CSI_ave_anova <- aov_ez('sbj',
'CSI_ave', ans_df,
within = c('arousal'), between = c('group', 'starting'))
CSI_ave_afex_plot <-
afex_plot(
CSI_ave_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(CSI_ave_afex_plot))
Code
print(CSI_ave_anova)Anova Table (Type 3 tests)
Response: CSI_ave
Effect df MSE F ges p.value
1 group 1, 6 0.10 0.02 .003 .901
2 starting 1, 6 0.10 0.31 .049 .599
3 group:starting 1, 6 0.10 0.07 .011 .806
4 arousal 1, 6 0.00 2.67 <.001 .153
5 group:arousal 1, 6 0.00 14.53 ** .001 .009
6 starting:arousal 1, 6 0.00 26.59 ** .002 .002
7 group:starting:arousal 1, 6 0.00 0.07 <.001 .794
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(CSI_ave_anova)____________________________________________________________
$emmeans
group arousal emmean SE df lower.CL upper.CL
control high 2.20 0.0973 6 1.96 2.44
study high 2.21 0.1300 6 1.89 2.52
control low 2.19 0.0989 6 1.95 2.43
study low 2.23 0.1320 6 1.90 2.55
Results are averaged over the levels of: starting
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control high - study high -0.00665 0.16200 6 -0.041 1.0000
control high - control low 0.00838 0.00462 6 1.815 0.3518
control high - study low -0.02760 0.16400 6 -0.168 0.9981
study high - control low 0.01503 0.16300 6 0.092 0.9997
study high - study low -0.02095 0.00615 6 -3.404 0.0535
control low - study low -0.03598 0.16500 6 -0.218 0.9959
Results are averaged over the levels of: starting
P value adjustment: tukey method for comparing a family of 4 estimates
____________________________________________________________
$emmeans
starting arousal emmean SE df lower.CL upper.CL
HA high 2.15 0.126 6 1.84 2.46
LA high 2.26 0.103 6 2.01 2.51
HA low 2.17 0.128 6 1.86 2.49
LA low 2.24 0.104 6 1.99 2.50
Results are averaged over the levels of: group
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
HA high - LA high -0.1105 0.16200 6 -0.681 0.9005
HA high - HA low -0.0261 0.00596 6 -4.383 0.0181
HA high - LA low -0.0970 0.16300 6 -0.594 0.9303
LA high - HA low 0.0844 0.16400 6 0.515 0.9523
LA high - LA low 0.0135 0.00487 6 2.785 0.1114
HA low - LA low -0.0709 0.16500 6 -0.430 0.9711
Results are averaged over the levels of: group
P value adjustment: tukey method for comparing a family of 4 estimates CPI_ave
3 middle minutes in each block to avoid block transitions
Code
CPI_ave_anova <- aov_ez('sbj',
'CPI_ave', ans_df,
within = c('arousal'), between = c('group', 'starting'))
CPI_ave_afex_plot <-
afex_plot(
CPI_ave_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(CPI_ave_afex_plot))
Code
print(CPI_ave_anova)Anova Table (Type 3 tests)
Response: CPI_ave
Effect df MSE F ges p.value
1 group 1, 6 0.27 0.00 <.001 .996
2 starting 1, 6 0.27 0.08 .014 .782
3 group:starting 1, 6 0.27 0.03 .005 .862
4 arousal 1, 6 0.00 0.52 <.001 .500
5 group:arousal 1, 6 0.00 0.47 <.001 .519
6 starting:arousal 1, 6 0.00 3.49 .005 .111
7 group:starting:arousal 1, 6 0.00 0.08 <.001 .781
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(CPI_ave_anova)SAI_ave
3 middle minutes in each block to avoid block transitions
Code
SAI_ave_anova <- aov_ez('sbj',
'SAI_ave', ans_df,
within = c('arousal'), between = c('group', 'starting'))
SAI_ave_afex_plot <-
afex_plot(
SAI_ave_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(SAI_ave_afex_plot))
Code
print(SAI_ave_anova)Anova Table (Type 3 tests)
Response: SAI_ave
Effect df MSE F ges p.value
1 group 1, 6 1065.29 0.00 <.001 .976
2 starting 1, 6 1065.29 0.00 <.001 .953
3 group:starting 1, 6 1065.29 0.01 .001 .938
4 arousal 1, 6 2.40 2.28 <.001 .182
5 group:arousal 1, 6 2.40 0.80 <.001 .407
6 starting:arousal 1, 6 2.40 11.09 * .004 .016
7 group:starting:arousal 1, 6 2.40 1.27 <.001 .302
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(SAI_ave_anova)____________________________________________________________
$emmeans
starting arousal emmean SE df lower.CL upper.CL
HA high 56.3 13.1 6 24.2 88.3
LA high 59.9 10.7 6 33.7 86.1
HA low 60.1 12.7 6 29.0 91.2
LA low 58.5 10.4 6 33.1 83.9
Results are averaged over the levels of: group
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
HA high - LA high -3.663 16.90 6 -0.216 0.9960
HA high - HA low -3.830 1.23 6 -3.125 0.0742
HA high - LA low -2.223 16.70 6 -0.133 0.9991
LA high - HA low -0.167 16.60 6 -0.010 1.0000
LA high - LA low 1.440 1.00 6 1.439 0.5226
HA low - LA low 1.607 16.40 6 0.098 0.9996
Results are averaged over the levels of: group
P value adjustment: tukey method for comparing a family of 4 estimates PAI_ave
3 middle minutes in each block to avoid block transitions
Code
PAI_ave_anova <- aov_ez('sbj',
'PAI_ave', ans_df,
within = c('arousal'), between = c('group', 'starting'))
PAI_ave_afex_plot <-
afex_plot(
PAI_ave_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(PAI_ave_afex_plot))
Code
print(PAI_ave_anova)Anova Table (Type 3 tests)
Response: PAI_ave
Effect df MSE F ges p.value
1 group 1, 6 488.20 0.01 .001 .935
2 starting 1, 6 488.20 0.10 .016 .762
3 group:starting 1, 6 488.20 0.35 .053 .577
4 arousal 1, 6 18.84 0.20 .001 .669
5 group:arousal 1, 6 18.84 0.02 <.001 .898
6 starting:arousal 1, 6 18.84 0.07 <.001 .797
7 group:starting:arousal 1, 6 18.84 0.03 <.001 .879
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(PAI_ave_anova)Frequency Domain HRV
HRV_LFn
Code
lfn_anova <- aov_ez('sbj',
'HRV_LFn', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
lfn_afex_plot <-
afex_plot(
lfn_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(lfn_afex_plot))
Code
print(lfn_anova)Anova Table (Type 3 tests)
Response: HRV_LFn
Effect df MSE F ges p.value
1 group 1, 6 0.13 0.01 .002 .926
2 starting 1, 6 0.13 0.48 .072 .514
3 group:starting 1, 6 0.13 0.02 .003 .902
4 arousal 1, 6 0.00 0.01 <.001 .933
5 group:arousal 1, 6 0.00 0.34 .002 .579
6 starting:arousal 1, 6 0.00 0.78 .004 .411
7 group:starting:arousal 1, 6 0.00 0.04 <.001 .856
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(lfn_anova)HRV_HFn
Code
hfn_anova <- aov_ez('sbj',
'HRV_HFn', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
hfn_afex_plot <-
afex_plot(
hfn_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hfn_afex_plot))
Code
print(hfn_anova)Anova Table (Type 3 tests)
Response: HRV_HFn
Effect df MSE F ges p.value
1 group 1, 6 0.09 0.03 .005 .872
2 starting 1, 6 0.09 0.57 .085 .478
3 group:starting 1, 6 0.09 0.08 .013 .788
4 arousal 1, 6 0.00 0.02 <.001 .895
5 group:arousal 1, 6 0.00 0.26 .001 .629
6 starting:arousal 1, 6 0.00 3.49 .014 .111
7 group:starting:arousal 1, 6 0.00 4.17 + .016 .087
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(hfn_anova)HRV_lnLF_lnHF
Code
hrv_df$HRV_lnLF_lnHF <- log(hrv_df$HRV_LFn) - log(hrv_df$HRV_HFn)
lfhf_anova <- aov_ez('sbj',
'HRV_lnLF_lnHF', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
lfhf_afex_plot <-
afex_plot(
lfhf_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(lfhf_afex_plot))
Code
print(lfhf_anova)Anova Table (Type 3 tests)
Response: HRV_lnLF_lnHF
Effect df MSE F ges p.value
1 group 1, 6 3.51 0.00 <.001 .950
2 starting 1, 6 3.51 0.64 .095 .455
3 group:starting 1, 6 3.51 0.00 <.001 .962
4 arousal 1, 6 0.05 0.10 <.001 .757
5 group:arousal 1, 6 0.05 0.09 <.001 .769
6 starting:arousal 1, 6 0.05 3.14 .007 .127
7 group:starting:arousal 1, 6 0.05 2.74 .006 .149
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(lfhf_anova)HR to HRV Ratio
Code
hrv_df$hr_to_hrv <- hrv_df$heart_rate / hrv_df$HRV_LFn
hr_to_hrv_anova <- aov_ez('sbj',
'hr_to_hrv', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
hr_to_hrv_afex_plot <-
afex_plot(
hr_to_hrv_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hr_to_hrv_afex_plot))
Code
print(hr_to_hrv_anova)Anova Table (Type 3 tests)
Response: hr_to_hrv
Effect df MSE F ges p.value
1 group 1, 6 25379.78 0.28 .043 .617
2 starting 1, 6 25379.78 0.60 .089 .467
3 group:starting 1, 6 25379.78 0.01 .002 .922
4 arousal 1, 6 728.41 0.68 .003 .440
5 group:arousal 1, 6 728.41 0.07 <.001 .804
6 starting:arousal 1, 6 728.41 0.01 <.001 .935
7 group:starting:arousal 1, 6 728.41 1.06 .005 .343
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(hr_to_hrv_anova)HR Periodic Components, greater peak
HR Frequency
Code
hr_frequency_anova <- aov_ez('sbj',
'frequency', hr_pow_peaks_df[hr_pow_peaks_df$peak_size == 1, ],
within = c('arousal'), between = c('group', 'starting'))
hr_frequency_afex_plot <-
afex_plot(
hr_frequency_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hr_frequency_afex_plot))
Code
print(hr_frequency_anova)Anova Table (Type 3 tests)
Response: frequency
Effect df MSE F ges p.value
1 group 1, 6 0.01 3.54 .346 .109
2 starting 1, 6 0.01 0.28 .040 .614
3 group:starting 1, 6 0.01 1.35 .167 .290
4 arousal 1, 6 0.00 0.37 .006 .566
5 group:arousal 1, 6 0.00 1.03 .018 .349
6 starting:arousal 1, 6 0.00 0.49 .008 .508
7 group:starting:arousal 1, 6 0.00 0.43 .007 .536
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(hr_frequency_anova)HR Power
Code
hr_power_anova <- aov_ez('sbj',
'power', hr_pow_peaks_df[hr_pow_peaks_df$peak_size == 1, ],
within = c('arousal'), between = c('group', 'starting'))
hr_power_afex_plot <-
afex_plot(
hr_power_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hr_power_afex_plot))
Code
print(hr_power_anova)Anova Table (Type 3 tests)
Response: power
Effect df MSE F ges p.value
1 group 1, 6 0.05 1.55 .155 .260
2 starting 1, 6 0.05 0.83 .090 .396
3 group:starting 1, 6 0.05 0.89 .095 .383
4 arousal 1, 6 0.02 0.05 .002 .829
5 group:arousal 1, 6 0.02 0.31 .015 .595
6 starting:arousal 1, 6 0.02 0.01 <.001 .932
7 group:starting:arousal 1, 6 0.02 0.89 .041 .381
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(hr_power_anova)HR Aperiodic Components
HR Exponent
Code
hr_exponent_anova <- aov_ez('sbj',
'exponent', hr_aperiodic_df,
within = c('arousal'), between = c('group', 'starting'))
hr_exponent_afex_plot <-
afex_plot(
hr_exponent_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hr_exponent_afex_plot))
Code
print(hr_exponent_anova)Anova Table (Type 3 tests)
Response: exponent
Effect df MSE F ges p.value
1 group 1, 6 1.62 0.55 .079 .486
2 starting 1, 6 1.62 0.78 .108 .412
3 group:starting 1, 6 1.62 0.15 .023 .708
4 arousal 1, 6 0.11 0.02 <.001 .896
5 group:arousal 1, 6 0.11 0.00 <.001 .983
6 starting:arousal 1, 6 0.11 1.27 .013 .303
7 group:starting:arousal 1, 6 0.11 2.20 .022 .189
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(hr_exponent_anova)HR Knee
Code
if('knee' %in% colnames(hr_aperiodic_df)) {
hr_knee_anova <- aov_ez('sbj',
'knee', hr_aperiodic_df,
within = c('arousal'), between = c('group', 'starting'))
hr_knee_afex_plot <-
afex_plot(
hr_knee_anova,
x = 'arousal',
trace = 'starting',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hr_knee_afex_plot))
} else {
print('Fitted with fixed mode, no knee parameter included.')
}
Code
if('knee' %in% colnames(hr_aperiodic_df)) {
print(hr_knee_anova)
a_posteriori(hr_knee_anova)
} else {
print('Fitted with fixed mode, no knee parameter included.')
}Anova Table (Type 3 tests)
Response: knee
Effect df MSE F ges p.value
1 group 1, 6 0.00 0.14 .022 .722
2 starting 1, 6 0.00 2.14 .260 .194
3 group:starting 1, 6 0.00 0.09 .014 .779
4 arousal 1, 6 0.00 2.12 .006 .196
5 group:arousal 1, 6 0.00 11.63 * .030 .014
6 starting:arousal 1, 6 0.00 2.94 .008 .137
7 group:starting:arousal 1, 6 0.00 6.87 * .018 .040
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
____________________________________________________________
$emmeans
group arousal emmean SE df lower.CL upper.CL
control high 0.000605 0.000257 6 -2.46e-05 0.00123
study high 0.000579 0.000343 6 -2.60e-04 0.00142
control low 0.000501 0.000243 6 -9.42e-05 0.00110
study low 0.000836 0.000325 6 4.17e-05 0.00163
Results are averaged over the levels of: starting
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control high - study high 2.56e-05 4.29e-04 6 0.060 0.9999
control high - control low 1.03e-04 6.34e-05 6 1.630 0.4304
control high - study low -2.31e-04 4.14e-04 6 -0.558 0.9409
study high - control low 7.76e-05 4.21e-04 6 0.185 0.9975
study high - study low -2.57e-04 8.45e-05 6 -3.041 0.0819
control low - study low -3.34e-04 4.06e-04 6 -0.824 0.8414
Results are averaged over the levels of: starting
P value adjustment: tukey method for comparing a family of 4 estimates
____________________________________________________________
$emmeans
group starting arousal emmean SE df lower.CL upper.CL
control HA high 0.000871 0.000297 6 1.44e-04 0.00160
study HA high 0.000828 0.000594 6 -6.25e-04 0.00228
control LA high 0.000339 0.000420 6 -6.89e-04 0.00137
study LA high 0.000330 0.000343 6 -5.09e-04 0.00117
control HA low 0.000719 0.000281 6 3.16e-05 0.00141
study HA low 0.001314 0.000562 6 -6.18e-05 0.00269
control LA low 0.000283 0.000398 6 -6.89e-04 0.00126
study LA low 0.000358 0.000325 6 -4.36e-04 0.00115
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control HA high - study HA high 4.24e-05 6.64e-04 6 0.064 1.0000
control HA high - control LA high 5.32e-04 5.14e-04 6 1.034 0.9510
control HA high - study LA high 5.41e-04 4.54e-04 6 1.192 0.9086
control HA high - control HA low 1.51e-04 7.32e-05 6 2.066 0.5137
control HA high - study HA low -4.43e-04 6.36e-04 6 -0.697 0.9937
control HA high - control LA low 5.87e-04 4.96e-04 6 1.183 0.9113
control HA high - study LA low 5.13e-04 4.40e-04 6 1.165 0.9168
study HA high - control LA high 4.89e-04 7.27e-04 6 0.673 0.9949
study HA high - study LA high 4.98e-04 6.86e-04 6 0.727 0.9921
study HA high - control HA low 1.09e-04 6.57e-04 6 0.165 1.0000
study HA high - study HA low -4.86e-04 1.46e-04 6 -3.320 0.1426
study HA high - control LA low 5.45e-04 7.15e-04 6 0.762 0.9896
study HA high - study LA low 4.70e-04 6.77e-04 6 0.695 0.9938
control LA high - study LA high 8.91e-06 5.42e-04 6 0.016 1.0000
control LA high - control HA low -3.81e-04 5.05e-04 6 -0.753 0.9903
control LA high - study HA low -9.75e-04 7.02e-04 6 -1.389 0.8355
control LA high - control LA low 5.54e-05 1.03e-04 6 0.535 0.9987
control LA high - study LA low -1.91e-05 5.31e-04 6 -0.036 1.0000
study LA high - control HA low -3.90e-04 4.43e-04 6 -0.878 0.9779
study LA high - study HA low -9.84e-04 6.59e-04 6 -1.494 0.7896
study LA high - control LA low 4.65e-05 5.25e-04 6 0.088 1.0000
study LA high - study LA low -2.80e-05 8.45e-05 6 -0.332 0.9999
control HA low - study HA low -5.94e-04 6.29e-04 6 -0.946 0.9680
control HA low - control LA low 4.36e-04 4.87e-04 6 0.895 0.9756
control HA low - study LA low 3.62e-04 4.29e-04 6 0.842 0.9823
study HA low - control LA low 1.03e-03 6.89e-04 6 1.496 0.7886
study HA low - study LA low 9.56e-04 6.49e-04 6 1.472 0.7994
control LA low - study LA low -7.45e-05 5.13e-04 6 -0.145 1.0000
P value adjustment: tukey method for comparing a family of 8 estimates HR Offset
Code
hr_offset_anova <- aov_ez('sbj',
'offset', hr_aperiodic_df,
within = c('arousal'), between = c('group', 'starting'))
hr_offset_afex_plot <-
afex_plot(
hr_offset_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(hr_offset_afex_plot))
Code
print(hr_offset_anova)Anova Table (Type 3 tests)
Response: offset
Effect df MSE F ges p.value
1 group 1, 6 0.47 0.88 .123 .385
2 starting 1, 6 0.47 0.82 .115 .400
3 group:starting 1, 6 0.47 0.00 <.001 .953
4 arousal 1, 6 0.02 0.13 <.001 .728
5 group:arousal 1, 6 0.02 0.19 .001 .682
6 starting:arousal 1, 6 0.02 0.06 <.001 .821
7 group:starting:arousal 1, 6 0.02 2.98 .021 .135
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(hr_offset_anova)Poincaré Plot HRV
HRV_SD2
Code
sd2_anova <- aov_ez('sbj',
'HRV_SD2', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
sd2_afex_plot <-
afex_plot(
sd2_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(sd2_afex_plot))
Code
print(sd2_anova)Anova Table (Type 3 tests)
Response: HRV_SD2
Effect df MSE F ges p.value
1 group 1, 6 1879.15 0.08 .014 .781
2 starting 1, 6 1879.15 0.39 .061 .553
3 group:starting 1, 6 1879.15 0.00 <.001 .990
4 arousal 1, 6 24.37 0.02 <.001 .893
5 group:arousal 1, 6 24.37 1.18 .003 .319
6 starting:arousal 1, 6 24.37 0.71 .002 .431
7 group:starting:arousal 1, 6 24.37 4.67 + .010 .074
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(sd2_anova)HRV_SD1SD2
Code
sd1sd2_anova <- aov_ez('sbj',
'HRV_SD1SD2', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
sd1sd2_afex_plot <-
afex_plot(
sd1sd2_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(sd1sd2_afex_plot))
Code
print(sd1sd2_anova)Anova Table (Type 3 tests)
Response: HRV_SD1SD2
Effect df MSE F ges p.value
1 group 1, 6 0.03 0.00 <.001 .987
2 starting 1, 6 0.03 0.40 .062 .548
3 group:starting 1, 6 0.03 0.03 .004 .874
4 arousal 1, 6 0.00 0.34 .002 .583
5 group:arousal 1, 6 0.00 0.30 .001 .604
6 starting:arousal 1, 6 0.00 3.05 .014 .131
7 group:starting:arousal 1, 6 0.00 6.39 * .028 .045
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(sd1sd2_anova)____________________________________________________________
$emmeans
group starting arousal emmean SE df lower.CL upper.CL
control HA high 0.427 0.0618 6 0.276 0.578
study HA high 0.399 0.1240 6 0.096 0.701
control LA high 0.327 0.0875 6 0.113 0.541
study LA high 0.342 0.0714 6 0.168 0.517
control HA low 0.351 0.0560 6 0.214 0.488
study HA low 0.409 0.1120 6 0.135 0.683
control LA low 0.371 0.0792 6 0.177 0.565
study LA low 0.331 0.0647 6 0.173 0.489
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control HA high - study HA high 0.02818 0.1380 6 0.204 1.0000
control HA high - control LA high 0.09988 0.1070 6 0.932 0.9701
control HA high - study LA high 0.08440 0.0945 6 0.893 0.9759
control HA high - control HA low 0.07623 0.0196 6 3.898 0.0776
control HA high - study HA low 0.01759 0.1280 6 0.137 1.0000
control HA high - control LA low 0.05548 0.1010 6 0.552 0.9984
control HA high - study LA low 0.09589 0.0895 6 1.071 0.9423
study HA high - control LA high 0.07171 0.1510 6 0.473 0.9994
study HA high - study LA high 0.05623 0.1430 6 0.394 0.9998
study HA high - control HA low 0.04805 0.1360 6 0.354 0.9999
study HA high - study HA low -0.01059 0.0391 6 -0.271 1.0000
study HA high - control LA low 0.02731 0.1470 6 0.186 1.0000
study HA high - study LA low 0.06772 0.1400 6 0.485 0.9993
control LA high - study LA high -0.01548 0.1130 6 -0.137 1.0000
control LA high - control HA low -0.02366 0.1040 6 -0.228 1.0000
control LA high - study HA low -0.08230 0.1420 6 -0.579 0.9979
control LA high - control LA low -0.04440 0.0277 6 -1.605 0.7373
control LA high - study LA low -0.00399 0.1090 6 -0.037 1.0000
study LA high - control HA low -0.00818 0.0908 6 -0.090 1.0000
study LA high - study HA low -0.06682 0.1330 6 -0.503 0.9991
study LA high - control LA low -0.02892 0.1070 6 -0.271 1.0000
study LA high - study LA low 0.01149 0.0226 6 0.509 0.9991
control HA low - study HA low -0.05864 0.1250 6 -0.468 0.9994
control HA low - control LA low -0.02075 0.0970 6 -0.214 1.0000
control HA low - study LA low 0.01966 0.0856 6 0.230 1.0000
study HA low - control LA low 0.03789 0.1370 6 0.276 1.0000
study HA low - study LA low 0.07830 0.1290 6 0.605 0.9973
control LA low - study LA low 0.04041 0.1020 6 0.395 0.9998
P value adjustment: tukey method for comparing a family of 8 estimates Heart Rate Fragmentation (HRF)
Percentage of inflection points of the RR intervals series (PIP)
Code
pip_anova <- aov_ez('sbj',
'HRF_PIP', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
pip_afex_plot <-
afex_plot(
pip_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(pip_afex_plot))
Code
print(pip_anova)Anova Table (Type 3 tests)
Response: HRF_PIP
Effect df MSE F ges p.value
1 group 1, 6 0.02 1.61 .210 .252
2 starting 1, 6 0.02 0.11 .018 .753
3 group:starting 1, 6 0.02 0.97 .138 .363
4 arousal 1, 6 0.00 0.26 <.001 .631
5 group:arousal 1, 6 0.00 0.29 <.001 .612
6 starting:arousal 1, 6 0.00 4.99 + .008 .067
7 group:starting:arousal 1, 6 0.00 1.08 .002 .339
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(pip_anova)Inverse of the average length of the acceleration/deceleration segments (IALS)
Code
ials_anova <- aov_ez('sbj',
'HRF_IALS', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
ials_afex_plot <-
afex_plot(
ials_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(ials_afex_plot))
Code
print(ials_anova)Anova Table (Type 3 tests)
Response: HRF_IALS
Effect df MSE F ges p.value
1 group 1, 6 0.02 1.61 .210 .252
2 starting 1, 6 0.02 0.10 .017 .760
3 group:starting 1, 6 0.02 0.91 .131 .377
4 arousal 1, 6 0.00 0.11 <.001 .753
5 group:arousal 1, 6 0.00 0.33 <.001 .588
6 starting:arousal 1, 6 0.00 4.57 + .007 .076
7 group:starting:arousal 1, 6 0.00 0.85 .001 .392
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(ials_anova)Percentage of short segments (PSS)
Code
pss_anova <- aov_ez('sbj',
'HRF_PSS', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
pss_afex_plot <-
afex_plot(
pss_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(pss_afex_plot))
Code
print(pss_anova)Anova Table (Type 3 tests)
Response: HRF_PSS
Effect df MSE F ges p.value
1 group 1, 6 0.09 1.10 .153 .335
2 starting 1, 6 0.09 0.05 .008 .836
3 group:starting 1, 6 0.09 0.67 .100 .443
4 arousal 1, 6 0.00 0.16 <.001 .707
5 group:arousal 1, 6 0.00 0.86 .002 .388
6 starting:arousal 1, 6 0.00 0.17 <.001 .697
7 group:starting:arousal 1, 6 0.00 1.42 .003 .278
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(pss_anova)Percentage of NN intervals in alternation segments (PAS)
Code
pas_anova <- aov_ez('sbj',
'HRF_PAS', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
pas_afex_plot <-
afex_plot(
pas_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(pas_afex_plot))
Code
print(pas_anova)Anova Table (Type 3 tests)
Response: HRF_PAS
Effect df MSE F ges p.value
1 group 1, 6 0.00 0.51 .075 .503
2 starting 1, 6 0.00 0.02 .004 .884
3 group:starting 1, 6 0.00 0.76 .109 .416
4 arousal 1, 6 0.00 0.25 .002 .632
5 group:arousal 1, 6 0.00 0.14 <.001 .723
6 starting:arousal 1, 6 0.00 0.10 <.001 .761
7 group:starting:arousal 1, 6 0.00 0.61 .004 .466
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(pas_anova)Heart Rate Asymmetry (HRA)
Guzik’s Index (GI)
Code
gi_anova <- aov_ez('sbj',
'HRA_GI', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
gi_afex_plot <-
afex_plot(
gi_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(gi_afex_plot))
Code
print(gi_anova)Anova Table (Type 3 tests)
Response: HRA_GI
Effect df MSE F ges p.value
1 group 1, 6 0.02 0.17 .008 .692
2 starting 1, 6 0.02 1.50 .065 .267
3 group:starting 1, 6 0.02 3.12 .126 .128
4 arousal 1, 6 0.06 2.67 .243 .154
5 group:arousal 1, 6 0.06 0.08 .009 .792
6 starting:arousal 1, 6 0.06 4.45 + .349 .079
7 group:starting:arousal 1, 6 0.06 0.00 <.001 .963
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(gi_anova)Slope Index (SI)
Code
si_anova <- aov_ez('sbj',
'HRA_SI', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
si_afex_plot <-
afex_plot(
si_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(si_afex_plot))
Code
print(si_anova)Anova Table (Type 3 tests)
Response: HRA_SI
Effect df MSE F ges p.value
1 group 1, 6 0.03 0.11 .006 .749
2 starting 1, 6 0.03 1.42 .070 .279
3 group:starting 1, 6 0.03 2.61 .121 .157
4 arousal 1, 6 0.06 2.64 .231 .155
5 group:arousal 1, 6 0.06 0.14 .016 .722
6 starting:arousal 1, 6 0.06 4.62 + .345 .075
7 group:starting:arousal 1, 6 0.06 0.01 <.001 .941
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(si_anova)Area Index (AI)
Code
ai_anova <- aov_ez('sbj',
'HRA_AI', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
ai_afex_plot <-
afex_plot(
ai_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(ai_afex_plot))
Code
print(ai_anova)Anova Table (Type 3 tests)
Response: HRA_AI
Effect df MSE F ges p.value
1 group 1, 6 0.02 0.28 .011 .618
2 starting 1, 6 0.02 1.58 .058 .256
3 group:starting 1, 6 0.02 3.88 + .133 .096
4 arousal 1, 6 0.06 2.70 .256 .151
5 group:arousal 1, 6 0.06 0.03 .004 .866
6 starting:arousal 1, 6 0.06 4.32 + .355 .083
7 group:starting:arousal 1, 6 0.06 0.00 <.001 .987
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(ai_anova)Porta’s Index (PI)
Code
pi_anova <- aov_ez('sbj',
'HRA_PI', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
pi_afex_plot <-
afex_plot(
pi_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(pi_afex_plot))
Code
print(pi_anova)Anova Table (Type 3 tests)
Response: HRA_PI
Effect df MSE F ges p.value
1 group 1, 6 69.50 0.01 <.001 .943
2 starting 1, 6 69.50 0.58 .086 .475
3 group:starting 1, 6 69.50 0.09 .014 .778
4 arousal 1, 6 1.63 2.09 .008 .198
5 group:arousal 1, 6 1.63 1.51 .006 .265
6 starting:arousal 1, 6 1.63 0.06 <.001 .809
7 group:starting:arousal 1, 6 1.63 2.12 .008 .195
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(pi_anova)Total variance of contributions of decelerations (SDNNd)
Code
sdnnd_anova <- aov_ez('sbj',
'HRA_SDNNd', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
sdnnd_afex_plot <-
afex_plot(
sdnnd_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(sdnnd_afex_plot))
Code
print(sdnnd_anova)Anova Table (Type 3 tests)
Response: HRA_SDNNd
Effect df MSE F ges p.value
1 group 1, 6 561.41 0.06 .009 .817
2 starting 1, 6 561.41 0.29 .046 .607
3 group:starting 1, 6 561.41 0.00 <.001 .969
4 arousal 1, 6 12.55 0.30 .001 .606
5 group:arousal 1, 6 12.55 0.30 .001 .602
6 starting:arousal 1, 6 12.55 1.11 .004 .332
7 group:starting:arousal 1, 6 12.55 1.50 .005 .267
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(sdnnd_anova)Total variance of contributions of accelerations (SDNNa)
Code
sdnna_anova <- aov_ez('sbj',
'HRA_SDNNa', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
sdnna_afex_plot <-
afex_plot(
sdnnd_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(sdnna_afex_plot))
Code
print(sdnna_anova)Anova Table (Type 3 tests)
Response: HRA_SDNNa
Effect df MSE F ges p.value
1 group 1, 6 632.55 0.09 .015 .770
2 starting 1, 6 632.55 0.28 .044 .615
3 group:starting 1, 6 632.55 0.00 <.001 .983
4 arousal 1, 6 7.52 0.01 <.001 .919
5 group:arousal 1, 6 7.52 1.47 .003 .271
6 starting:arousal 1, 6 7.52 0.66 .001 .448
7 group:starting:arousal 1, 6 7.52 3.20 .006 .124
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(sdnna_anova)Indices of Complexity
HRV_SampEn
Code
sampen_anova <- aov_ez('sbj',
'HRV_SampEn', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
sampen_afex_plot <-
afex_plot(
sampen_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(sampen_afex_plot))
Code
print(sampen_anova)Anova Table (Type 3 tests)
Response: HRV_SampEn
Effect df MSE F ges p.value
1 group 1, 6 0.15 3.63 .360 .106
2 starting 1, 6 0.15 0.49 .071 .509
3 group:starting 1, 6 0.15 0.27 .041 .619
4 arousal 1, 6 0.01 0.95 .011 .367
5 group:arousal 1, 6 0.01 0.10 .001 .760
6 starting:arousal 1, 6 0.01 0.50 .006 .506
7 group:starting:arousal 1, 6 0.01 0.23 .003 .652
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(sampen_anova)HRV_ShanEn
Code
shanen_anova <- aov_ez('sbj',
'HRV_ShanEn', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
shanen_afex_plot <-
afex_plot(
shanen_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(shanen_afex_plot))
Code
print(shanen_anova)Anova Table (Type 3 tests)
Response: HRV_ShanEn
Effect df MSE F ges p.value
1 group 1, 6 0.35 0.00 <.001 .951
2 starting 1, 6 0.35 0.47 .071 .519
3 group:starting 1, 6 0.35 0.21 .033 .663
4 arousal 1, 6 0.01 0.06 <.001 .818
5 group:arousal 1, 6 0.01 3.36 .011 .116
6 starting:arousal 1, 6 0.01 1.43 .005 .277
7 group:starting:arousal 1, 6 0.01 6.65 * .021 .042
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(shanen_anova)____________________________________________________________
$emmeans
group starting arousal emmean SE df lower.CL upper.CL
control HA high 6.91 0.226 6 6.36 7.47
study HA high 7.22 0.451 6 6.12 8.33
control LA high 7.32 0.319 6 6.54 8.10
study LA high 7.13 0.260 6 6.49 7.77
control HA low 7.04 0.198 6 6.56 7.53
study HA low 6.97 0.396 6 6.00 7.94
control LA low 7.33 0.280 6 6.64 8.02
study LA low 7.20 0.229 6 6.64 7.76
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control HA high - study HA high -0.3089 0.5040 6 -0.613 0.9970
control HA high - control LA high -0.4058 0.3910 6 -1.039 0.9498
control HA high - study LA high -0.2154 0.3440 6 -0.625 0.9967
control HA high - control HA low -0.1277 0.0595 6 -2.147 0.4769
control HA high - study HA low -0.0580 0.4560 6 -0.127 1.0000
control HA high - control LA low -0.4149 0.3600 6 -1.154 0.9202
control HA high - study LA low -0.2883 0.3210 6 -0.898 0.9753
study HA high - control LA high -0.0969 0.5520 6 -0.175 1.0000
study HA high - study LA high 0.0935 0.5210 6 0.180 1.0000
study HA high - control HA low 0.1813 0.4930 6 0.368 0.9999
study HA high - study HA low 0.2510 0.1190 6 2.110 0.4933
study HA high - control LA low -0.1060 0.5310 6 -0.200 1.0000
study HA high - study LA low 0.0206 0.5060 6 0.041 1.0000
control LA high - study LA high 0.1904 0.4120 6 0.462 0.9995
control LA high - control HA low 0.2782 0.3750 6 0.741 0.9911
control LA high - study HA low 0.3479 0.5090 6 0.684 0.9944
control LA high - control LA low -0.0091 0.0841 6 -0.108 1.0000
control LA high - study LA low 0.1175 0.3920 6 0.299 1.0000
study LA high - control HA low 0.0877 0.3270 6 0.268 1.0000
study LA high - study HA low 0.1575 0.4740 6 0.332 0.9999
study LA high - control LA low -0.1995 0.3820 6 -0.522 0.9989
study LA high - study LA low -0.0729 0.0687 6 -1.062 0.9446
control HA low - study HA low 0.0697 0.4430 6 0.157 1.0000
control HA low - control LA low -0.2873 0.3430 6 -0.837 0.9828
control HA low - study LA low -0.1607 0.3030 6 -0.531 0.9988
study HA low - control LA low -0.3570 0.4850 6 -0.736 0.9915
study HA low - study LA low -0.2304 0.4570 6 -0.504 0.9991
control LA low - study LA low 0.1266 0.3620 6 0.350 0.9999
P value adjustment: tukey method for comparing a family of 8 estimates Respiratory Rate Variability (RRV)
Respiratory Rate
Code
hrv_df$rsp_rate <- 60000 / hrv_df$RRV_MeanBB
rsp_rate_anova <- aov_ez('sbj',
'rsp_rate', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
rsp_rate_afex_plot <-
afex_plot(
rsp_rate_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsp_rate_afex_plot))
Code
print(rsp_rate_anova)Anova Table (Type 3 tests)
Response: rsp_rate
Effect df MSE F ges p.value
1 group 1, 6 18.83 4.16 + .402 .087
2 starting 1, 6 18.83 0.17 .026 .697
3 group:starting 1, 6 18.83 2.46 .284 .168
4 arousal 1, 6 0.60 0.00 <.001 .995
5 group:arousal 1, 6 0.60 0.56 .003 .483
6 starting:arousal 1, 6 0.60 0.13 <.001 .728
7 group:starting:arousal 1, 6 0.60 0.11 <.001 .751
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsp_rate_anova)log10_RRV_RMSSD
Code
rrmssd_anova <- aov_ez('sbj',
'log10_RRV_RMSSD', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
rrmssd_afex_plot <-
afex_plot(
rrmssd_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rrmssd_afex_plot))
Code
print(rrmssd_anova)Anova Table (Type 3 tests)
Response: log10_RRV_RMSSD
Effect df MSE F ges p.value
1 group 1, 6 0.08 0.85 .115 .391
2 starting 1, 6 0.08 1.54 .190 .262
3 group:starting 1, 6 0.08 1.25 .161 .306
4 arousal 1, 6 0.01 0.00 <.001 .950
5 group:arousal 1, 6 0.01 0.08 .001 .792
6 starting:arousal 1, 6 0.01 0.81 .011 .403
7 group:starting:arousal 1, 6 0.01 0.68 .009 .443
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rrmssd_anova)RRV_SD2
Code
rrv_sd2_anova <- aov_ez('sbj',
'RRV_SD2', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
rrv_sd2_afex_plot <-
afex_plot(
rrv_sd2_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rrv_sd2_afex_plot))
Code
print(rrv_sd2_anova)Anova Table (Type 3 tests)
Response: RRV_SD2
Effect df MSE F ges p.value
1 group 1, 6 872621.74 0.52 .073 .499
2 starting 1, 6 872621.74 0.03 .004 .872
3 group:starting 1, 6 872621.74 0.11 .017 .750
4 arousal 1, 6 81190.91 0.16 .002 .702
5 group:arousal 1, 6 81190.91 0.01 <.001 .925
6 starting:arousal 1, 6 81190.91 1.40 .019 .282
7 group:starting:arousal 1, 6 81190.91 0.97 .014 .363
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rrv_sd2_anova)RRV_SD2SD1
Code
RRV_SD2SD1_anova <- aov_ez('sbj',
'RRV_SD2SD1', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
RRV_SD2SD1_afex_plot <-
afex_plot(
RRV_SD2SD1_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(RRV_SD2SD1_afex_plot))
Code
print(RRV_SD2SD1_anova)Anova Table (Type 3 tests)
Response: RRV_SD2SD1
Effect df MSE F ges p.value
1 group 1, 6 0.07 0.21 .022 .660
2 starting 1, 6 0.07 4.79 + .333 .071
3 group:starting 1, 6 0.07 1.54 .138 .261
4 arousal 1, 6 0.04 0.09 .006 .774
5 group:arousal 1, 6 0.04 0.01 <.001 .928
6 starting:arousal 1, 6 0.04 0.00 <.001 .967
7 group:starting:arousal 1, 6 0.04 0.05 .003 .836
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(RRV_SD2SD1_anova)RRV_ApEn
Code
RRV_ApEn_anova <- aov_ez('sbj',
'RRV_ApEn', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
RRV_ApEn_afex_plot <-
afex_plot(
RRV_ApEn_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(RRV_ApEn_afex_plot))
Code
print(RRV_ApEn_anova)Anova Table (Type 3 tests)
Response: RRV_ApEn
Effect df MSE F ges p.value
1 group 1, 6 0.05 4.31 + .408 .083
2 starting 1, 6 0.05 1.62 .206 .250
3 group:starting 1, 6 0.05 0.58 .084 .476
4 arousal 1, 6 0.00 0.10 <.001 .760
5 group:arousal 1, 6 0.00 0.01 <.001 .934
6 starting:arousal 1, 6 0.00 1.01 .007 .353
7 group:starting:arousal 1, 6 0.00 0.00 <.001 .961
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(RRV_ApEn_anova)RSP Periodic Components, greater peak
RSP Frequency
Code
rsp_frequency_anova <- aov_ez('sbj',
'frequency', rsp_pow_peaks_df[rsp_pow_peaks_df$peak_size == 1, ],
within = c('arousal'), between = c('group', 'starting'))
rsp_frequency_afex_plot <-
afex_plot(
rsp_frequency_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsp_frequency_afex_plot))
Code
print(rsp_frequency_anova)Anova Table (Type 3 tests)
Response: frequency
Effect df MSE F ges p.value
1 group 1, 6 0.01 2.11 .258 .197
2 starting 1, 6 0.01 0.51 .077 .503
3 group:starting 1, 6 0.01 0.67 .100 .444
4 arousal 1, 6 0.00 0.06 <.001 .816
5 group:arousal 1, 6 0.00 0.53 <.001 .495
6 starting:arousal 1, 6 0.00 1.10 .002 .335
7 group:starting:arousal 1, 6 0.00 2.55 .004 .161
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsp_frequency_anova)RSP Power
Code
rsp_power_anova <- aov_ez('sbj',
'power', rsp_pow_peaks_df[rsp_pow_peaks_df$peak_size == 1, ],
within = c('arousal'), between = c('group', 'starting'))
rsp_power_afex_plot <-
afex_plot(
rsp_power_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsp_power_afex_plot))
Code
print(rsp_power_anova)Anova Table (Type 3 tests)
Response: power
Effect df MSE F ges p.value
1 group 1, 6 0.11 4.03 + .337 .091
2 starting 1, 6 0.11 0.34 .042 .579
3 group:starting 1, 6 0.11 0.02 .002 .905
4 arousal 1, 6 0.04 0.42 .017 .540
5 group:arousal 1, 6 0.04 2.12 .080 .195
6 starting:arousal 1, 6 0.04 0.08 .003 .788
7 group:starting:arousal 1, 6 0.04 4.58 + .157 .076
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsp_power_anova)RSP Aperiodic Components
RSP Exponent
Code
rsp_exponent_anova <- aov_ez('sbj',
'exponent', rsp_aperiodic_df,
within = c('arousal'), between = c('group', 'starting'))
rsp_exponent_afex_plot <-
afex_plot(
rsp_exponent_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsp_exponent_afex_plot))
Code
print(rsp_exponent_anova)Anova Table (Type 3 tests)
Response: exponent
Effect df MSE F ges p.value
1 group 1, 6 6.40 1.68 .126 .242
2 starting 1, 6 6.40 0.10 .009 .762
3 group:starting 1, 6 6.40 4.75 + .288 .072
4 arousal 1, 6 6.09 1.72 .123 .237
5 group:arousal 1, 6 6.09 0.00 <.001 .997
6 starting:arousal 1, 6 6.09 0.00 <.001 .954
7 group:starting:arousal 1, 6 6.09 1.80 .127 .228
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsp_exponent_anova)RSP Knee
Code
if('knee' %in% colnames(rsp_aperiodic_df)) {
rsp_knee_anova <- aov_ez('sbj',
'knee', rsp_aperiodic_df,
within = c('arousal'), between = c('group', 'starting'))
rsp_knee_afex_plot <-
afex_plot(
rsp_knee_anova,
x = 'arousal',
trace = 'starting',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsp_knee_afex_plot))
} else {
print('Fitted with fixed mode, no knee parameter included.')
}
Code
if('knee' %in% colnames(rsp_aperiodic_df)) {
print(rsp_knee_anova)
a_posteriori(rsp_knee_anova)
} else {
print('Fitted with fixed mode, no knee parameter included.')
}Anova Table (Type 3 tests)
Response: knee
Effect df MSE F ges p.value
1 group 1, 6 4979.29 1.29 .131 .299
2 starting 1, 6 4979.29 0.17 .020 .690
3 group:starting 1, 6 4979.29 0.10 .012 .762
4 arousal 1, 6 2124.13 6.99 * .258 .038
5 group:arousal 1, 6 2124.13 2.05 .093 .202
6 starting:arousal 1, 6 2124.13 0.11 .005 .752
7 group:starting:arousal 1, 6 2124.13 1.04 .049 .348
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1
____________________________________________________________
$emmeans
arousal emmean SE df lower.CL upper.CL
high 6.27 7.53 6 -12.16 24.7
low 68.44 29.50 6 -3.65 140.5
Results are averaged over the levels of: group, starting
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
high - low -62.2 23.5 6 -2.644 0.0384
Results are averaged over the levels of: group, starting RSP Offset
Code
rsp_offset_anova <- aov_ez('sbj',
'offset', rsp_aperiodic_df,
within = c('arousal'), between = c('group', 'starting'))
rsp_offset_afex_plot <-
afex_plot(
rsp_offset_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsp_offset_afex_plot))
Code
print(rsp_offset_anova)Anova Table (Type 3 tests)
Response: offset
Effect df MSE F ges p.value
1 group 1, 6 2.63 1.00 .091 .355
2 starting 1, 6 2.63 0.07 .007 .797
3 group:starting 1, 6 2.63 6.59 * .396 .042
4 arousal 1, 6 1.78 2.16 .127 .192
5 group:arousal 1, 6 1.78 0.15 .010 .707
6 starting:arousal 1, 6 1.78 0.02 .001 .887
7 group:starting:arousal 1, 6 1.78 1.20 .075 .315
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsp_offset_anova)____________________________________________________________
$emmeans
group starting emmean SE df lower.CL upper.CL
control HA -1.333 0.573 6 -2.74 0.0697
study HA -2.629 1.150 6 -5.44 0.1764
control LA -3.236 0.811 6 -5.22 -1.2517
study LA -0.283 0.662 6 -1.90 1.3370
Results are averaged over the levels of: arousal
Confidence level used: 0.95
$contrasts
contrast estimate SE df t.ratio p.value
control HA - study HA 1.296 1.280 6 1.011 0.7497
control HA - control LA 1.902 0.993 6 1.916 0.3140
control HA - study LA -1.050 0.876 6 -1.199 0.6491
study HA - control LA 0.606 1.400 6 0.432 0.9708
study HA - study LA -2.346 1.320 6 -1.772 0.3690
control LA - study LA -2.953 1.050 6 -2.821 0.1067
Results are averaged over the levels of: arousal
P value adjustment: tukey method for comparing a family of 4 estimates Respiratory Sinus Arrhythmia (RSA)
RSA_P2T_Mean
Code
rsa_p2t_anova <- aov_ez('sbj',
'RSA_P2T_Mean_log', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
rsa_p2t_afex_plot <-
afex_plot(
rsa_p2t_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsa_p2t_afex_plot))
Code
print(rsa_p2t_anova)Anova Table (Type 3 tests)
Response: RSA_P2T_Mean_log
Effect df MSE F ges p.value
1 group 1, 6 0.78 1.04 .145 .347
2 starting 1, 6 0.78 0.02 .004 .881
3 group:starting 1, 6 0.78 1.35 .181 .290
4 arousal 1, 6 0.01 0.00 <.001 .987
5 group:arousal 1, 6 0.01 0.48 .001 .515
6 starting:arousal 1, 6 0.01 1.70 .005 .240
7 group:starting:arousal 1, 6 0.01 0.15 <.001 .711
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsa_p2t_anova)RSA_PorgesBohrer
Code
rsa_pogboh_anova <- aov_ez('sbj',
'RSA_PorgesBohrer', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
rsa_pogboh_afex_plot <-
afex_plot(
rsa_pogboh_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsa_pogboh_afex_plot))
Code
print(rsa_pogboh_anova)Anova Table (Type 3 tests)
Response: RSA_PorgesBohrer
Effect df MSE F ges p.value
1 group 1, 6 1.75 0.11 .018 .748
2 starting 1, 6 1.75 0.12 .019 .744
3 group:starting 1, 6 1.75 1.01 .140 .353
4 arousal 1, 6 0.06 0.14 <.001 .720
5 group:arousal 1, 6 0.06 0.02 <.001 .900
6 starting:arousal 1, 6 0.06 0.84 .004 .394
7 group:starting:arousal 1, 6 0.06 0.00 <.001 .991
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsa_pogboh_anova)RSA_Gates_Mean
Code
rsa_gates_anova <- aov_ez('sbj',
'RSA_Gates_Mean_log', hrv_df,
within = c('arousal'), between = c('group', 'starting'))
rsa_gates_afex_plot <-
afex_plot(
rsa_gates_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(rsa_gates_afex_plot))
Code
print(rsa_gates_anova)Anova Table (Type 3 tests)
Response: RSA_Gates_Mean_log
Effect df MSE F ges p.value
1 group 1, 6 0.01 0.05 .009 .823
2 starting 1, 6 0.01 0.09 .014 .777
3 group:starting 1, 6 0.01 0.00 <.001 .982
4 arousal 1, 6 0.00 0.89 .002 .382
5 group:arousal 1, 6 0.00 0.64 .001 .455
6 starting:arousal 1, 6 0.00 3.51 .007 .110
7 group:starting:arousal 1, 6 0.00 0.16 <.001 .705
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(rsa_gates_anova)RSP-HR Continuous Coherence, average
ccoh_ave_lfhf
Frequency range .04 - .4 Hz
3 middle minutes in each block to avoid block transitions
Code
ccoh_ave_lfhf_anova <- aov_ez('sbj',
'ccoh_ave_lfhf', ccoh_df,
within = c('arousal'), between = c('group', 'starting'))
ccoh_ave_lfhf_afex_plot <-
afex_plot(
ccoh_ave_lfhf_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(ccoh_ave_lfhf_afex_plot))
Code
print(ccoh_ave_lfhf_anova)Anova Table (Type 3 tests)
Response: ccoh_ave_lfhf
Effect df MSE F ges p.value
1 group 1, 6 0.01 0.20 .026 .674
2 starting 1, 6 0.01 0.28 .037 .614
3 group:starting 1, 6 0.01 0.64 .080 .456
4 arousal 1, 6 0.00 0.02 <.001 .888
5 group:arousal 1, 6 0.00 0.93 .028 .372
6 starting:arousal 1, 6 0.00 2.79 .079 .146
7 group:starting:arousal 1, 6 0.00 0.04 .001 .855
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(ccoh_ave_lfhf_anova)ccoh_ave_rsp
Frequency band of .15 Hz around subject modal respiratory frequency
3 middle minutes in each block to avoid block transitions
Code
ccoh_ave_rsp_anova <- aov_ez('sbj',
'ccoh_ave_rsp', ccoh_df,
within = c('arousal'), between = c('group', 'starting'))
ccoh_ave_rsp_afex_plot <-
afex_plot(
ccoh_ave_rsp_anova,
x = 'starting',
trace = 'arousal',
panel = 'group',
error = 'within',
error_arg = list(width = .15),
dodge = my_dodge,
data_arg = list(
position =
position_jitterdodge(
jitter.width = .1,
dodge.width = my_dodge
)),
mapping = c('color'),
point_arg = list(size = 4)
)
suppressWarnings(print(ccoh_ave_rsp_afex_plot))
Code
print(ccoh_ave_rsp_anova)Anova Table (Type 3 tests)
Response: ccoh_ave_rsp
Effect df MSE F ges p.value
1 group 1, 6 0.01 0.48 .063 .516
2 starting 1, 6 0.01 0.31 .042 .597
3 group:starting 1, 6 0.01 0.35 .046 .578
4 arousal 1, 6 0.00 0.78 .020 .411
5 group:arousal 1, 6 0.00 3.67 .090 .104
6 starting:arousal 1, 6 0.00 3.83 + .093 .098
7 group:starting:arousal 1, 6 0.00 0.92 .024 .375
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1Code
a_posteriori(ccoh_ave_rsp_anova)