knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(rstatix)
library(lsr)
library(ggpubr)
library(flextable)
library(emmeans)
library(tableone)

Dataset Upload

Demographics

vars <- c("age", "gender")
cat <- c("gender")
demotable <- CreateTableOne(vars = vars, data = demo, factorVars = cat)
demotable

##                  
##                   Overall      
##   n                  30        
##   age (mean (SD)) 24.37 (5.77) 
##   gender = m (%)     13 (43.3)

Parietal

#tidy data

GD_parietal <- grad_double |>
  mutate( #Mutate new value for alpha modulation proportion against neutral condition

# Left Hemisphere    
    Left_Parietal_ROI_Left_Attention_stim_Double = 
      (`Left-parietal_ROI_left_attention` - `Left-parietal_ROI_neutral_attention`)/(`Left-parietal_ROI_left_attention`+`Left-parietal_ROI_neutral_attention`),
    
    Left_Parietal_ROI_Right_Attention_stim_Double = (`Left-parietal_ROI_right_attention`-`Left-parietal_ROI_neutral_attention`)/(`Left-parietal_ROI_right_attention`+`Left-parietal_ROI_neutral_attention`),

# Right Hemisphere    
    Right_Parietal_ROI_Left_Attention_stim_Double = (`Right-parietal_ROI_left_attention`-`Right-parietal_ROI_neutral_attention`)/(`Right-parietal_ROI_left_attention`+`Right-parietal_ROI_neutral_attention`),
    
    Right_Parietal_ROI_Right_Attention_stim_Double = (`Right-parietal_ROI_right_attention`-`Right-parietal_ROI_neutral_attention`)/(`Right-parietal_ROI_right_attention`+`Right-parietal_ROI_neutral_attention`)) |>
  select(1,
         "Left_Parietal_ROI_Left_Attention_stim_Double", 
         "Left_Parietal_ROI_Right_Attention_stim_Double",
         "Right_Parietal_ROI_Left_Attention_stim_Double",
         "Right_Parietal_ROI_Right_Attention_stim_Double") 


GN_parietal <- grad_nostim |>
  mutate( #Mutate new value for alpha modulation proportion against neutral condition
    Left_Parietal_ROI_Left_Attention_stim_NoStim = 
      (`Left-parietal_ROI_left_attention` - `Left-parietal_ROI_neutral_attention`)/(`Left-parietal_ROI_left_attention`+`Left-parietal_ROI_neutral_attention`),
    Left_Parietal_ROI_Right_Attention_stim_NoStim = (`Left-parietal_ROI_right_attention`-`Left-parietal_ROI_neutral_attention`)/(`Left-parietal_ROI_right_attention`+`Left-parietal_ROI_neutral_attention`),
    Right_Parietal_ROI_Left_Attention_stim_NoStim = (`Right-parietal_ROI_left_attention`-`Right-parietal_ROI_neutral_attention`)/(`Right-parietal_ROI_left_attention`+`Right-parietal_ROI_neutral_attention`),
    Right_Parietal_ROI_Right_Attention_stim_NoStim = (`Right-parietal_ROI_right_attention`-`Right-parietal_ROI_neutral_attention`)/(`Right-parietal_ROI_right_attention`+`Right-parietal_ROI_neutral_attention`)) |>
  select(1,
         "Left_Parietal_ROI_Left_Attention_stim_NoStim", 
         "Left_Parietal_ROI_Right_Attention_stim_NoStim",
         "Right_Parietal_ROI_Left_Attention_stim_NoStim",
         "Right_Parietal_ROI_Right_Attention_stim_NoStim")


all_stim_parietal <- 
  full_join(GD_parietal, GN_parietal, by = "...1") 
  
#Convert to long formata for analysis
grad_parietal <- pivot_longer(all_stim_parietal,
  cols = c(Left_Parietal_ROI_Left_Attention_stim_Double:Right_Parietal_ROI_Right_Attention_stim_NoStim),
  names_to = c("hemisphere", "attention", "stimulus"),
  names_pattern = "(.*)_ROI_(.*)_stim_(.*)",
  values_to = "alpha")

Summary Descriptive

#Mean / SD for alpha value
grad_parietal|>
  group_by(hemisphere, attention, stimulus) |>
  get_summary_stats(alpha, type = "mean_sd") |>
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    attention = "Attention",
                    stimulus = "Stimulus", 
                    variable = "Variable")

Hemisphere	Attention	Stimulus	Variable	n	mean	sd
Left_Parietal	Left_Attention	Double	alpha	30	0.008	0.039
Left_Parietal	Left_Attention	NoStim	alpha	30	0.011	0.038
Left_Parietal	Right_Attention	Double	alpha	30	-0.011	0.041
Left_Parietal	Right_Attention	NoStim	alpha	30	-0.015	0.037
Right_Parietal	Left_Attention	Double	alpha	30	-0.010	0.040
Right_Parietal	Left_Attention	NoStim	alpha	30	-0.010	0.038
Right_Parietal	Right_Attention	Double	alpha	30	0.017	0.040
Right_Parietal	Right_Attention	NoStim	alpha	30	0.022	0.039

Outliers

#To identify outliers
grad_parietal|>
  group_by(hemisphere, attention, stimulus) |>
  identify_outliers(alpha) |>
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    attention = "Attention",
                    stimulus = "Stimulus",
                    ...1 = "ID",
                    alpha = "Alpha")

Hemisphere	Attention	Stimulus	ID	Alpha	is.outlier	is.extreme
Left_Parietal	Left_Attention	Double	S009_fha01	0.07892581	TRUE	FALSE
Left_Parietal	Left_Attention	Double	S015_csi07	-0.09326127	TRUE	FALSE
Left_Parietal	Left_Attention	Double	S018_ade02	-0.05267781	TRUE	FALSE
Left_Parietal	Left_Attention	Double	S028_omr03	-0.08087781	TRUE	FALSE
Left_Parietal	Right_Attention	NoStim	S027_fmn28	-0.13610540	TRUE	TRUE
Right_Parietal	Left_Attention	Double	S028_omr03	-0.11255864	TRUE	FALSE
Right_Parietal	Right_Attention	Double	S026_dja01	0.12442160	TRUE	FALSE
Right_Parietal	Right_Attention	NoStim	S019_dtl05	-0.09752286	TRUE	FALSE

QQ

#Residual QQ plot
qq_p  <- lm(alpha ~ hemisphere*attention*stimulus, data=grad_parietal) 
ggqqplot(residuals(qq_p))

Normality With Stimulus

#Normality testing
grad_parietal|>
  group_by(hemisphere, attention, stimulus) |>
  shapiro_test(alpha) |> #must be P >.05
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    attention = "Attention",
                    stimulus = "Stimulus", 
                    variable = "Variable",
                    statistic = "Statistics")

Hemisphere	Attention	Stimulus	Variable	Statistics	p
Left_Parietal	Left_Attention	Double	alpha	0.9402059	0.09212739
Left_Parietal	Left_Attention	NoStim	alpha	0.9585659	0.28456791
Left_Parietal	Right_Attention	Double	alpha	0.9907699	0.99438757
Left_Parietal	Right_Attention	NoStim	alpha	0.9266838	0.04011766
Right_Parietal	Left_Attention	Double	alpha	0.9341299	0.06327180
Right_Parietal	Left_Attention	NoStim	alpha	0.9757527	0.70490248
Right_Parietal	Right_Attention	Double	alpha	0.9583086	0.28024089
Right_Parietal	Right_Attention	NoStim	alpha	0.9412470	0.09827434

Normality Without Stimulus

#Normality test above speculates stimulus affected normality, this is to test nromality without taking into account stimulus
grad_parietal|>
  select(-c("stimulus")) |>
  group_by(hemisphere, attention) |>
  shapiro_test(alpha) |> #must be P >.05
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    attention = "Attention",
                    variable = "Variables",
                    Sstatistics = "Statistics")

Hemisphere	Attention	Variables	statistic	p
Left_Parietal	Left_Attention	alpha	0.9792159	0.3962772
Left_Parietal	Right_Attention	alpha	0.9859400	0.7188646
Right_Parietal	Left_Attention	alpha	0.9749632	0.2532652
Right_Parietal	Right_Attention	alpha	0.9765110	0.2991998

ANOVA Hemisphere X Attention X Stimulus

#ANOVA Test
anova_test(grad_parietal, 
           dv = alpha, 
           wid = ...1,
           within = c(hemisphere, attention, stimulus),
           effect.size = "pes") |>
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(pes = "Effect Size (ƞ2p)")

Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
hemisphere	1	29	2.144	0.15400000000		0.069
attention	1	29	0.473	0.49700000000		0.016
stimulus	1	29	0.039	0.84500000000		0.001
hemisphere:attention	1	29	67.704	0.00000000451	*	0.700
hemisphere:stimulus	1	29	0.258	0.61500000000		0.009
attention:stimulus	1	29	0.055	0.81700000000		0.002
hemisphere:attention:stimulus	1	29	2.327	0.13800000000		0.074

#Cohen's D Benchmarks
#.01: Small effect size
#.06: Medium effect size
#.14 or higher: Large effect size

ANOVA Without Outliers

#ANOVA for removed extreme outliers
grad_parietal_rm <- grad_parietal |>
  filter(!...1 == "S027_fmn28") #enter extreme outliers here

anova_test(grad_parietal_rm, 
           dv = alpha, 
           wid = ...1,
           within = c(hemisphere, attention, stimulus),
           effect.size = "pes") |>
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(pes = "Effect Size (ƞ2p)")

Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
hemisphere	1	28	1.099	0.30300000000		0.038
attention	1	28	0.630	0.43400000000		0.022
stimulus	1	28	0.210	0.65000000000		0.007
hemisphere:attention	1	28	74.886	0.00000000212	*	0.728
hemisphere:stimulus	1	28	0.093	0.76300000000		0.003
attention:stimulus	1	28	0.132	0.71900000000		0.005
hemisphere:attention:stimulus	1	28	1.372	0.25100000000		0.047

#.01: Small effect size
#.06: Medium effect size
#.14 or higher: Large effect size

Mean Compare

#Tidy data for averaged stimulus types

G_all_p <- all_stim_parietal |>
  mutate(
    Left_Parietal_ROI_Left_Attention = 
      ((`Left_Parietal_ROI_Left_Attention_stim_Double` + `Left_Parietal_ROI_Left_Attention_stim_NoStim`)/2),
  
    Left_Parietal_ROI_Right_Attention = 
      ((`Left_Parietal_ROI_Right_Attention_stim_Double` + `Left_Parietal_ROI_Right_Attention_stim_NoStim`)/2),
    
    Right_Parietal_ROI_Left_Attention = 
      ((`Right_Parietal_ROI_Left_Attention_stim_Double` + `Right_Parietal_ROI_Left_Attention_stim_NoStim`)/2),
   
    Right_Parietal_ROI_Right_Attention = 
      ((`Right_Parietal_ROI_Right_Attention_stim_Double` + `Right_Parietal_ROI_Right_Attention_stim_NoStim`)/2)) |>
      
  select(1,
         "Left_Parietal_ROI_Left_Attention", 
         "Left_Parietal_ROI_Right_Attention",
         "Right_Parietal_ROI_Left_Attention",
         "Right_Parietal_ROI_Right_Attention")

One Sample t-test

#T-tests for each interaction modulation from neutral baseline
t1_p <- t.test(G_all_p$"Left_Parietal_ROI_Left_Attention",
           mu = 0,
           alternative = "greater")
t1_p_mean <- mean(G_all_p$Left_Parietal_ROI_Left_Attention)
t1_p_sd <- sd(G_all_p$Left_Parietal_ROI_Left_Attention)
t1_p_es <- cohensD(G_all_p$Left_Parietal_ROI_Left_Attention, mu = 0)

t2_p <- t.test(G_all_p$"Left_Parietal_ROI_Right_Attention",
           mu = 0,
           alternative = "less")
t2_p_mean <- mean(G_all_p$Left_Parietal_ROI_Right_Attention)
t2_p_sd <- sd(G_all_p$Left_Parietal_ROI_Right_Attention)
t2_p_es <- cohensD(G_all_p$Left_Parietal_ROI_Right_Attention, mu = 0)


t3_p <- t.test(G_all_p$"Right_Parietal_ROI_Left_Attention",
           mu = 0,
           alternative = "less")
t3_p_mean <- mean(G_all_p$Right_Parietal_ROI_Left_Attention)
t3_p_sd <- sd(G_all_p$Right_Parietal_ROI_Left_Attention)
t3_p_es <- cohensD(G_all_p$Right_Parietal_ROI_Left_Attention, mu = 0)


t4_p <- t.test(G_all_p$"Right_Parietal_ROI_Right_Attention",
           mu = 0,
           alternative = "greater")
t4_p_mean <- mean(G_all_p$Right_Parietal_ROI_Right_Attention)
t4_p_sd <- sd(G_all_p$Right_Parietal_ROI_Right_Attention)
t4_p_es <- cohensD(G_all_p$Right_Parietal_ROI_Right_Attention, mu = 0)

t_p_table <- map_df(list(t1_p, t2_p, t3_p, t4_p), tidy) 

mutate(t_p_table,
       "t-test Comparison" = c("Left Hemisphere - Left Attention", 
                          "Left Hemisphere - Right Attention",
                          "Right Hemisphere - Left Attention",
                          "Right Hemisphere - Right Attention"),
       "Standard Deviation" = c(t1_p_sd,
                                t2_p_sd,
                                t3_p_sd,
                                t4_p_sd),
       "Effect Size (d)" = c(t1_p_es,
                         t2_p_es,
                         t3_p_es,
                         t4_p_es))|>
  subset(select=c(9, 1, 10, 2, 3, 4, 5, 6, 7, 8, 11)) |>
  flextable (cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(estimate = "Estimate",
                    statistic = "Statistic",
                    p.value = "P Value",
                    parameter = "Parameter")

t-test Comparison	Estimate	Standard Deviation	Statistic	P Value	Parameter	conf.low	conf.high	method	alternative	Effect Size (d)
Left Hemisphere - Left Attention	0.009179950	0.03280938	1.532509	0.068117370	29	-0.000998068	Inf	One Sample t-test	greater	0.2797965
Left Hemisphere - Right Attention	-0.012647025	0.03277551	-2.113487	0.021640931	29	-Inf	-0.0024795123	One Sample t-test	less	0.3858681
Right Hemisphere - Left Attention	-0.009816692	0.03364550	-1.598081	0.060432651	29	-Inf	0.0006207052	One Sample t-test	less	0.2917683
Right Hemisphere - Right Attention	0.019661449	0.03346623	3.217877	0.001585087	29	0.009279665	Inf	One Sample t-test	greater	0.5875012

Post Hoc

hemisphere:attention significancy in D/N

# any significance towards stimulus? (is hemisphere:attention significant in both D/N)
PH_1_parietal <- grad_parietal |>
  group_by(stimulus) |>
  anova_test(dv = alpha, 
             wid = ...1, 
             within = c(hemisphere, attention),
             effect.size = "pes")
flextable(PH_1_parietal,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(stimulus = "Stimulus",
                    pes = "Effect Size (ƞ2p)")

Stimulus	Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
Double	hemisphere	1	29	1.043	0.3160000000		0.035
Double	attention	1	29	0.727	0.4010000000		0.024
Double	hemisphere:attention	1	29	45.188	0.0000002240	*	0.609
NoStim	hemisphere	1	29	1.959	0.1720000000		0.063
NoStim	attention	1	29	0.198	0.6600000000		0.007
NoStim	hemisphere:attention	1	29	52.831	0.0000000527	*	0.646

Effects of 2 Levels of Hemisphere

# Effects of 2 Levels of Hemisphere
PH_2_parietal <- grad_parietal |>
  group_by(stimulus, hemisphere) |>
  anova_test(dv = alpha, 
             wid = ...1, 
             within = attention,
             effect.size = "pes")

flextable(PH_2_parietal,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    stimulus = "Stimulus",
                    pes = "Effect Size (ƞ2p)")

Hemisphere	Stimulus	Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
Left_Parietal	Double	attention	1	29	11.026	0.002000	*	0.275
Right_Parietal	Double	attention	1	29	15.322	0.000505	*	0.346
Left_Parietal	NoStim	attention	1	29	10.580	0.003000	*	0.267
Right_Parietal	NoStim	attention	1	29	14.271	0.000729	*	0.330

Effects of 2 Levels of Attention

# Effects of 2 Levels of Attention
PH_3_parietal <- grad_parietal |>
  group_by(stimulus, attention) |>
  anova_test(dv = alpha, 
             wid = ...1, 
             within = hemisphere,
             effect.size = "pes")

flextable(PH_3_parietal,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(attention = "Attention",
                    stimulus = "Stimulus", 
                    pes = "Effect Size (ƞ2p)")

Attention	Stimulus	Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
Left_Attention	Double	hemisphere	1	29	13.946	0.000819	*	0.325
Right_Attention	Double	hemisphere	1	29	15.167	0.000532	*	0.343
Left_Attention	NoStim	hemisphere	1	29	13.997	0.000804	*	0.326
Right_Attention	NoStim	hemisphere	1	29	19.445	0.000130	*	0.401

Effects of 2 Levels of Stimulus

# Effects of 2 Levels of Stimulus
PH_4_parietal <- grad_parietal |>
  group_by(attention, hemisphere) |>
  anova_test(dv = alpha, 
             wid = ...1, 
             within = stimulus,
             effect.size = "pes")

flextable(PH_4_parietal,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    attention = "Attention",
                    pes = "Effect Size (ƞ2p)")

Hemisphere	Attention	Effect	DFn	DFd	F	p	Effect Size (ƞ2p)
Left_Parietal	Left_Attention	stimulus	1	29	0.206	0.653	0.007000
Right_Parietal	Left_Attention	stimulus	1	29	0.003	0.957	0.000102
Left_Parietal	Right_Attention	stimulus	1	29	0.282	0.600	0.010000
Right_Parietal	Right_Attention	stimulus	1	29	0.423	0.520	0.014000

Pairwise Comparison 1

#Pairwise comparisons of 2 levels of attention within hemisphere
pw_comp_1 <- grad_parietal |>
  group_by(stimulus, hemisphere) |>
  pairwise_t_test(alpha ~ attention, 
                  paired = TRUE, 
                  p.adjust.method = "bonferroni")
flextable(pw_comp_1,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    stimulus = "Stimulus",
                    .y. = "Variable")

Hemisphere	Stimulus	Variable	group1	group2	n1	n2	statistic	df	p	p.adj	p.adj.signif
Left_Parietal	Double	alpha	Left_Attention	Right_Attention	30	30	3.320548	29	0.002000	0.002000	**
Right_Parietal	Double	alpha	Left_Attention	Right_Attention	30	30	-3.914373	29	0.000505	0.000505	***
Left_Parietal	NoStim	alpha	Left_Attention	Right_Attention	30	30	3.252641	29	0.003000	0.003000	**
Right_Parietal	NoStim	alpha	Left_Attention	Right_Attention	30	30	-3.777759	29	0.000729	0.000729	***

Pairwise Comparison 2

#Pairwise comparisons of 2 levels of hemisphere within attention
pw_comp_2 <- grad_parietal |>
  group_by(stimulus, attention) |>
  pairwise_t_test(alpha ~ hemisphere, 
                  paired = TRUE, 
                  p.adjust.method = "bonferroni")
flextable(pw_comp_2,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(attention = "Attention",
                    stimulus = "Stimulus",
                    .y. = "Variable")

Attention	Stimulus	Variable	group1	group2	n1	n2	statistic	df	p	p.adj	p.adj.signif
Left_Attention	Double	alpha	Left_Parietal	Right_Parietal	30	30	3.734408	29	0.000819	0.000819	***
Right_Attention	Double	alpha	Left_Parietal	Right_Parietal	30	30	-3.894424	29	0.000532	0.000532	***
Left_Attention	NoStim	alpha	Left_Parietal	Right_Parietal	30	30	3.741255	29	0.000804	0.000804	***
Right_Attention	NoStim	alpha	Left_Parietal	Right_Parietal	30	30	-4.409685	29	0.000130	0.000130	***

Occipital

GD_occipital <- grad_double |>
  mutate(
    Left_Occipital_ROI_Left_Attention_stim_Double = 
      (`Left-occipital_ROI_left_attention` - `Left-occipital_ROI_neutral_attention`)/(`Left-occipital_ROI_left_attention`+`Left-occipital_ROI_neutral_attention`),
    Left_Occipital_ROI_Right_Attention_stim_Double = (`Left-occipital_ROI_right_attention`-`Left-occipital_ROI_neutral_attention`)/(`Left-occipital_ROI_right_attention`+`Left-occipital_ROI_neutral_attention`),
    Right_Occipital_ROI_Left_Attention_stim_Double = (`Right-occipital_ROI_left_attention`-`Right-occipital_ROI_neutral_attention`)/(`Right-occipital_ROI_left_attention`+`Right-occipital_ROI_neutral_attention`),
    Right_Occipital_ROI_Right_Attention_stim_Double = (`Right-occipital_ROI_right_attention`-`Right-occipital_ROI_neutral_attention`)/(`Right-occipital_ROI_right_attention`+`Right-occipital_ROI_neutral_attention`)) |>
  select(1,
         "Left_Occipital_ROI_Left_Attention_stim_Double", 
         "Left_Occipital_ROI_Right_Attention_stim_Double",
         "Right_Occipital_ROI_Left_Attention_stim_Double",
         "Right_Occipital_ROI_Right_Attention_stim_Double")


GN_occipital <- grad_nostim |>
  mutate(
    Left_Occipital_ROI_Left_Attention_stim_NoStim = 
      (`Left-occipital_ROI_left_attention` - `Left-occipital_ROI_neutral_attention`)/(`Left-occipital_ROI_left_attention`+`Left-occipital_ROI_neutral_attention`),
    Left_Occipital_ROI_Right_Attention_stim_NoStim = (`Left-occipital_ROI_right_attention`-`Left-occipital_ROI_neutral_attention`)/(`Left-occipital_ROI_right_attention`+`Left-occipital_ROI_neutral_attention`),
    Right_Occipital_ROI_Left_Attention_stim_NoStim = (`Right-occipital_ROI_left_attention`-`Right-occipital_ROI_neutral_attention`)/(`Right-occipital_ROI_left_attention`+`Right-occipital_ROI_neutral_attention`),
    Right_Occipital_ROI_Right_Attention_stim_NoStim = (`Right-occipital_ROI_right_attention`-`Right-occipital_ROI_neutral_attention`)/(`Right-occipital_ROI_right_attention`+`Right-occipital_ROI_neutral_attention`)) |>
  select(1,
         "Left_Occipital_ROI_Left_Attention_stim_NoStim", 
         "Left_Occipital_ROI_Right_Attention_stim_NoStim",
         "Right_Occipital_ROI_Left_Attention_stim_NoStim",
         "Right_Occipital_ROI_Right_Attention_stim_NoStim")


all_stim_occipital <- 
  full_join(GD_occipital, GN_occipital, by = "...1") 
  

grad_occipital <- pivot_longer(all_stim_occipital,
  cols = c(Left_Occipital_ROI_Left_Attention_stim_Double:Right_Occipital_ROI_Right_Attention_stim_NoStim),
  names_to = c("hemisphere", "attention", "stimulus"),
  names_pattern = "(.*)_ROI_(.*)_stim_(.*)",
  values_to = "alpha")

Summary Descriptive

grad_occipital|>
  group_by(hemisphere, attention, stimulus) |>
  get_summary_stats(alpha, type = "mean_sd") |>
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    attention = "Attention",
                    stimulus = "Stimulus", 
                    variable = "Variable")

Hemisphere	Attention	Stimulus	Variable	n	mean	sd
Left_Occipital	Left_Attention	Double	alpha	30	0.047	0.032
Left_Occipital	Left_Attention	NoStim	alpha	30	0.053	0.046
Left_Occipital	Right_Attention	Double	alpha	30	0.006	0.039
Left_Occipital	Right_Attention	NoStim	alpha	30	0.004	0.045
Right_Occipital	Left_Attention	Double	alpha	30	0.014	0.037
Right_Occipital	Left_Attention	NoStim	alpha	30	0.009	0.037
Right_Occipital	Right_Attention	Double	alpha	30	0.040	0.043
Right_Occipital	Right_Attention	NoStim	alpha	30	0.059	0.060

Outliers

grad_occipital|>
  group_by(hemisphere, attention, stimulus) |>
  identify_outliers(alpha) |>
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere", 
                    attention = "Attention", 
                    stimulus = "Stimulis",
                    ...1 = "ID",
                    alpha = "Alpha")

Hemisphere	Attention	Stimulis	ID	Alpha	is.outlier	is.extreme
Left_Occipital	Right_Attention	NoStim	S009_fha01	-0.08771973	TRUE	FALSE
Right_Occipital	Left_Attention	Double	S021_jmn22	0.09280188	TRUE	FALSE
Right_Occipital	Right_Attention	NoStim	S022_dss19	0.20147397	TRUE	FALSE
Right_Occipital	Right_Attention	NoStim	S028_omr03	0.20064041	TRUE	FALSE

QQ

#Residual QQ
qq  <- lm(alpha ~ hemisphere*attention*stimulus, data=grad_occipital) 
ggqqplot(residuals(qq))

Normality

grad_occipital|>
  group_by(hemisphere, attention, stimulus) |>
  shapiro_test(alpha) |> #must be P >.05
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    attention = "Attention",
                    stimulus = "Stimulus", 
                    variable = "Variable",
                    statistic = "Statistics")

Hemisphere	Attention	Stimulus	Variable	Statistics	p
Left_Occipital	Left_Attention	Double	alpha	0.9585876	0.2849354
Left_Occipital	Left_Attention	NoStim	alpha	0.9630065	0.3688407
Left_Occipital	Right_Attention	Double	alpha	0.9742250	0.6599117
Left_Occipital	Right_Attention	NoStim	alpha	0.9621563	0.3512658
Right_Occipital	Left_Attention	Double	alpha	0.9734545	0.6373238
Right_Occipital	Left_Attention	NoStim	alpha	0.9503438	0.1726817
Right_Occipital	Right_Attention	Double	alpha	0.9684023	0.4964377
Right_Occipital	Right_Attention	NoStim	alpha	0.9532372	0.2062559

ANOVA

anova_test(grad_occipital, 
           dv = alpha, wid = ...1,
           within = c(hemisphere, attention, stimulus),
           effect.size = "pes") |>
  flextable(cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  colformat_double(digits = 3) |>
  set_header_labels(pes = "Effect Size (ƞ2p)")

Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
hemisphere	1.000	29.000	0.876	0.357		0.029
attention	1.000	29.000	0.489	0.490		0.017
stimulus	1.000	29.000	0.353	0.557		0.012
hemisphere:attention	1.000	29.000	113.547	0.000	*	0.797
hemisphere:stimulus	1.000	29.000	0.898	0.351		0.030
attention:stimulus	1.000	29.000	1.588	0.218		0.052
hemisphere:attention:stimulus	1.000	29.000	16.993	0.000	*	0.369

#.01: Small effect size
#.06: Medium effect size
#.14 or higher: Large effect size

Post Hoc

Simple Two way Interaction

# Simple Two way Interaction
PH_1_occipital <- grad_occipital%>%
  group_by(attention) %>%
  anova_test(dv = alpha, 
             wid = ...1, 
             within = c(stimulus, hemisphere),
             effect.size = "pes")
flextable(PH_1_occipital,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  colformat_double(digits = 3) |>
  set_header_labels(attention = "Attention",
                    pes = "Effect Size (ƞ2p)")

Attention	Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
Left_Attention	stimulus	1.000	29.000	0.003	0.955		0.000
Left_Attention	hemisphere	1.000	29.000	66.696	0.000	*	0.697
Left_Attention	stimulus:hemisphere	1.000	29.000	2.796	0.105		0.088
Right_Attention	stimulus	1.000	29.000	1.088	0.306		0.036
Right_Attention	hemisphere	1.000	29.000	63.481	0.000	*	0.686
Right_Attention	stimulus:hemisphere	1.000	29.000	7.719	0.009	*	0.210

Simple Simple Main Effect

#effect of attention
PH_2_occipital <- grad_occipital%>%
  group_by(stimulus, hemisphere) %>%
  anova_test(dv = alpha, 
             wid = ...1, 
             within = c(attention),
             effect.size = "pes")
flextable(PH_2_occipital,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  colformat_double(digits = 3) |>
  set_header_labels(attention = "Attention",
                    pes = "Effect Size (ƞ2p)")

hemisphere	stimulus	Effect	DFn	DFd	F	p	p<.05	Effect Size (ƞ2p)
Left_Occipital	Double	attention	1.000	29.000	36.712	0.000	*	0.559
Right_Occipital	Double	attention	1.000	29.000	13.598	0.001	*	0.319
Left_Occipital	NoStim	attention	1.000	29.000	40.592	0.000	*	0.583
Right_Occipital	NoStim	attention	1.000	29.000	26.085	0.000	*	0.474

Pairwise Comparison

#Pairwise comparisons
pw_occipital <- grad_occipital |>
  group_by(stimulus, hemisphere) |>
  pairwise_t_test(alpha ~ attention, #group1 vs group2
                  paired = TRUE, 
                  p.adjust.method = "bonferroni")
flextable(pw_occipital,
          cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(hemisphere = "Hemisphere",
                    stimulus = "Stimulus",
                    .y. = "Variable")

Hemisphere	Stimulus	Variable	group1	group2	n1	n2	statistic	df	p	p.adj	p.adj.signif
Left_Occipital	Double	alpha	Left_Attention	Right_Attention	30	30	6.059023	29	0.000001350	0.000001350	****
Right_Occipital	Double	alpha	Left_Attention	Right_Attention	30	30	-3.687508	29	0.000928000	0.000928000	***
Left_Occipital	NoStim	alpha	Left_Attention	Right_Attention	30	30	6.371193	29	0.000000578	0.000000578	****
Right_Occipital	NoStim	alpha	Left_Attention	Right_Attention	30	30	-5.107319	29	0.000018800	0.000018800	****

One Sample t-test

#Tidy Data for averaged stimulus

G_all_o <- all_stim_occipital |>
  mutate(
    Left_Occipital_ROI_Left_Attention = 
      ((`Left_Occipital_ROI_Left_Attention_stim_Double` + `Left_Occipital_ROI_Left_Attention_stim_NoStim`)/2),
  
    Left_Occipital_ROI_Right_Attention = 
      ((`Left_Occipital_ROI_Right_Attention_stim_Double` + `Left_Occipital_ROI_Right_Attention_stim_NoStim`)/2),
    
    Right_Occipital_ROI_Left_Attention = 
      ((`Right_Occipital_ROI_Left_Attention_stim_Double` + `Right_Occipital_ROI_Left_Attention_stim_NoStim`)/2),
   
    Right_Occipital_ROI_Right_Attention = 
      ((`Right_Occipital_ROI_Right_Attention_stim_Double` + `Right_Occipital_ROI_Right_Attention_stim_NoStim`)/2)) |>
      
  select(1,
         "Left_Occipital_ROI_Left_Attention", 
         "Left_Occipital_ROI_Right_Attention",
         "Right_Occipital_ROI_Left_Attention",
         "Right_Occipital_ROI_Right_Attention")

Double

t1_oD <- t.test(GD_occipital$"Left_Occipital_ROI_Left_Attention_stim_Double",
           mu = 0,
           alternative = "greater")
t1_oD_mean <- mean(GD_occipital$Left_Occipital_ROI_Left_Attention_stim_Double)
t1_oD_sd <- sd(GD_occipital$Left_Occipital_ROI_Left_Attention_stim_Double)
t1_oD_es <- cohensD(GD_occipital$Left_Occipital_ROI_Left_Attention_stim_Double, mu = 0)

t2_oD <- t.test(GD_occipital$"Left_Occipital_ROI_Right_Attention_stim_Double",
           mu = 0,
           alternative = "less")
t2_oD_mean <- mean(GD_occipital$Left_Occipital_ROI_Right_Attention_stim_Double)
t2_oD_sd <- sd(GD_occipital$Left_Occipital_ROI_Right_Attention_stim_Double)
t2_oD_es <- cohensD(GD_occipital$Left_Occipital_ROI_Right_Attention_stim_Double, mu = 0)


t3_oD <- t.test(GD_occipital$"Right_Occipital_ROI_Left_Attention_stim_Double",
           mu = 0,
           alternative = "less")
t3_oD_mean <- mean(GD_occipital$Right_Occipital_ROI_Left_Attention_stim_Double)
t3_oD_sd <- sd(GD_occipital$Right_Occipital_ROI_Left_Attention_stim_Double)
t3_oD_es <- cohensD(GD_occipital$Right_Occipital_ROI_Left_Attention_stim_Double, mu = 0)


t4_oD <- t.test(GD_occipital$"Right_Occipital_ROI_Right_Attention_stim_Double",
           mu = 0,
           alternative = "greater")
t4_oD_mean <- mean(GD_occipital$Right_Occipital_ROI_Right_Attention_stim_Double)
t4_oD_sd <- sd(GD_occipital$Right_Occipital_ROI_Right_Attention_stim_Double)
t4_oD_es <- cohensD(GD_occipital$Right_Occipital_ROI_Right_Attention_stim_Double, mu = 0)

t_oD_table <- map_df(list(t1_oD, t2_oD, t3_oD, t4_oD), tidy) 

mutate(t_oD_table,
       "t-test Comparison" = c("Left Hemisphere - Left Attention", 
                          "Left Hemisphere - Right Attention",
                          "Right Hemisphere - Left Attention",
                          "Right Hemisphere - Right Attention"),
       "Standard Deviation" = c(t1_oD_sd,
                                t2_oD_sd,
                                t3_oD_sd,
                                t4_oD_sd),
       "Effect Size (d)" = c(t1_oD_es,
                         t2_oD_es,
                         t3_oD_es,
                         t4_oD_es))|>
  subset(select=c(9, 1, 10, 2, 3, 4, 5, 6, 7, 8, 11)) |>
  flextable (cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(estimate = "Estimate",
                    statistic = "Statistic",
                    p.value = "P Value",
                    parameter = "Parameter")

t-test Comparison	Estimate	Standard Deviation	Statistic	P Value	Parameter	conf.low	conf.high	method	alternative	Effect Size (d)
Left Hemisphere - Left Attention	0.04737487	0.03150716	8.2356796	0.000000002214707	29	0.03760082	Inf	One Sample t-test	greater	1.5036225
Left Hemisphere - Right Attention	0.00564111	0.03912083	0.7897999	0.781972354616179	29	-Inf	0.01777705	One Sample t-test	less	0.1441971
Right Hemisphere - Left Attention	0.01418297	0.03669295	2.1171189	0.978526026664741	29	-Inf	0.02556574	One Sample t-test	less	0.3865313
Right Hemisphere - Right Attention	0.03955525	0.04273697	5.0694516	0.000010456360396	29	0.02629752	Inf	One Sample t-test	greater	0.9255510

NoStim

t1_oN <- t.test(GN_occipital$"Left_Occipital_ROI_Left_Attention_stim_NoStim",
           mu = 0,
           alternative = "greater")
t1_oN_mean <- mean(GN_occipital$Left_Occipital_ROI_Left_Attention_stim_NoStim)
t1_oN_sd <- sd(GN_occipital$Left_Occipital_ROI_Left_Attention_stim_NoStim)
t1_oN_es <- cohensD(GN_occipital$Left_Occipital_ROI_Left_Attention_stim_NoStim, mu = 0)

t2_oN <- t.test(GN_occipital$"Left_Occipital_ROI_Right_Attention_stim_NoStim",
           mu = 0,
           alternative = "less")
t2_oN_mean <- mean(GN_occipital$Left_Occipital_ROI_Right_Attention_stim_NoStim)
t2_oN_sd <- sd(GN_occipital$Left_Occipital_ROI_Right_Attention_stim_NoStim)
t2_oN_es <- cohensD(GN_occipital$Left_Occipital_ROI_Right_Attention_stim_NoStim, mu = 0)


t3_oN <- t.test(GN_occipital$"Right_Occipital_ROI_Left_Attention_stim_NoStim",
           mu = 0,
           alternative = "less")
t3_oN_mean <- mean(GN_occipital$Right_Occipital_ROI_Left_Attention_stim_NoStim)
t3_oN_sd <- sd(GN_occipital$Right_Occipital_ROI_Left_Attention_stim_NoStim)
t3_oN_es <- cohensD(GN_occipital$Right_Occipital_ROI_Left_Attention_stim_NoStim, mu = 0)


t4_oN <- t.test(GN_occipital$"Right_Occipital_ROI_Right_Attention_stim_NoStim",
           mu = 0,
           alternative = "greater")
t4_oN_mean <- mean(GN_occipital$Right_Occipital_ROI_Right_Attention_stim_NoStim)
t4_oN_sd <- sd(GN_occipital$Right_Occipital_ROI_Right_Attention_stim_NoStim)
t4_oN_es <- cohensD(GN_occipital$Right_Occipital_ROI_Right_Attention_stim_NoStim, mu = 0)

t_oN_table <- map_df(list(t1_oN, t2_oN, t3_oN, t4_oN), tidy) 

mutate(t_oN_table,
       "t-test Comparison" = c("Left Hemisphere - Left Attention", 
                          "Left Hemisphere - Right Attention",
                          "Right Hemisphere - Left Attention",
                          "Right Hemisphere - Right Attention"),
       "Standard Deviation" = c(t1_oN_sd,
                                t2_oN_sd,
                                t3_oN_sd,
                                t4_oN_sd),
       "Effect Size (d)" = c(t1_oN_es,
                         t2_oN_es,
                         t3_oN_es,
                         t4_oN_es))|>
  subset(select=c(9, 1, 10, 2, 3, 4, 5, 6, 7, 8, 11)) |>
  flextable (cwidth = .95) |>
  fontsize(size = 8) |>
  fontsize(size = 10, part = "header") |>
  set_header_labels(estimate = "Estimate",
                    statistic = "Statistic",
                    p.value = "P Value",
                    parameter = "Parameter")

t-test Comparison	Estimate	Standard Deviation	Statistic	P Value	Parameter	conf.low	conf.high	method	alternative	Effect Size (d)
Left Hemisphere - Left Attention	0.053178412	0.04629933	6.2910225	0.0000003595577	29	0.03881558	Inf	One Sample t-test	greater	1.14857832
Left Hemisphere - Right Attention	0.003500427	0.04457691	0.4301022	0.6648496702868	29	-Inf	0.01732893	One Sample t-test	less	0.07852556
Right Hemisphere - Left Attention	0.009350656	0.03706369	1.3818282	0.9112112877044	29	-Inf	0.02084843	One Sample t-test	less	0.25228616
Right Hemisphere - Right Attention	0.059405114	0.06008796	5.4149815	0.0000040043818	29	0.04076482	Inf	One Sample t-test	greater	0.98863584

Neutral vs No Attention

GD_parietal_NN <- grad_double |>
  mutate(Left_parietal_ROI_neutral_attention_stim_Double = `Left-parietal_ROI_neutral_attention`,
         Right_parietal_ROI_neutral_attention_stim_Double = `Right-parietal_ROI_neutral_attention`,
         Left_parietal_ROI_no_attention_stim_Double = `Left-parietal_ROI_no_attention`,
         Right_parietal_ROI_no_attention_stim_Double = `Right-parietal_ROI_no_attention`) |>
  select(1,
         "Left_parietal_ROI_neutral_attention_stim_Double",
         "Right_parietal_ROI_neutral_attention_stim_Double",
         "Left_parietal_ROI_no_attention_stim_Double",
         "Right_parietal_ROI_no_attention_stim_Double")
GN_parietal_NN <- grad_nostim |>
  mutate(Left_parietal_ROI_neutral_attention_stim_NoStim = `Left-parietal_ROI_neutral_attention`,
         Right_parietal_ROI_neutral_attention_stim_NoStim = `Right-parietal_ROI_neutral_attention`,
         Left_parietal_ROI_no_attention_stim_NoStim = `Left-parietal_ROI_no_attention`,
         Right_parietal_ROI_no_attention_stim_NoStim = `Right-parietal_ROI_no_attention`) |>
  select(1,
         "Left_parietal_ROI_neutral_attention_stim_NoStim",
         "Right_parietal_ROI_neutral_attention_stim_NoStim",
         "Left_parietal_ROI_no_attention_stim_NoStim",
         "Right_parietal_ROI_no_attention_stim_NoStim")

all_stim_parietal_NN <- 
  full_join(GD_parietal_NN, GN_parietal_NN, by = "...1") 
  

grad_parietal_NN <- pivot_longer(all_stim_parietal_NN,
  cols = c(Left_parietal_ROI_neutral_attention_stim_Double:Right_parietal_ROI_no_attention_stim_NoStim),
  names_to = c("hemisphere", "attention", "stimulus"),
  names_pattern = "(.*)_ROI_(.*)_stim_(.*)",
  values_to = "alpha")

ANOVA 7-12Hz

Leonardo Sutandi

2023-06-30

Dataset Upload

Demographics

Parietal

Summary Descriptive

Outliers

QQ

Normality With Stimulus

Normality Without Stimulus

ANOVA Hemisphere X Attention X Stimulus

ANOVA Without Outliers

Mean Compare

One Sample t-test

Post Hoc

hemisphere:attention significancy in D/N

Effects of 2 Levels of Hemisphere

Effects of 2 Levels of Attention

Effects of 2 Levels of Stimulus

Pairwise Comparison 1

Pairwise Comparison 2

Occipital

Summary Descriptive

Outliers

QQ

Normality

ANOVA

Post Hoc

Simple Two way Interaction

Simple Simple Main Effect

Pairwise Comparison

One Sample t-test

Double

NoStim

Neutral vs No Attention