EEG_temporal_reproduction/derivatives/preproc_data.R

library(tidyverse)
library(ez)
library(ggpubr)
library(rstatix)
library(lmerTest)        # lmer function
library(car)             # contr.Sum function
library(sjPlot)          # tab_model function
library(BayesFactor)
library(bayestestR) #Bayes factors (BFincl)
library(lme4) 
library(ggplot2)
library(grid)
library(gridExtra)
library(cowplot)
library(plyr)

colors_plot <- c("#3399CC", "#a3263d")
col11=c("#E34234","#6495ED")
colors3= c("#FF0000" ,"#FF7F50", "#FFBF00", "#40E0D0" ,"#6495ED", "#000080")

#customize theme
theme_new <- theme_bw() + 
  theme(panel.border = element_blank(), 
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), 
        axis.line=element_line(colour='black'),
        strip.background = element_rect(color = 'white', fill = 'white'),
        panel.grid = element_blank())+
  theme(axis.text.x = element_text(color = "black", size = 10), 
        axis.text.y = element_text(color = "black", size = 10), 
        axis.title.x = element_text(color = "black", size = 10, vjust = -1),
        axis.title.y = element_text(color = "black", size = 10),
        plot.title =element_text(size=10,face='bold'),
        legend.text=element_text(size=10)) 

theme_new2 <- theme_bw() + 
  theme(panel.border = element_blank(), 
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), 
        axis.line=element_line(colour='black'),
        strip.background = element_rect(color = 'white', fill = 'white'),
        panel.grid = element_blank())+
  theme(axis.text.x = element_text(color = "black", size = 12), 
        axis.text.y = element_text(color = "black", size = 12), 
        axis.title.x = element_text(color = "black", size = 12, vjust = -1),
        axis.title.y = element_text(color = "black", size = 12),
        plot.title =element_text(size=10,face='bold'),
        legend.text=element_text(size=11))

## load data
data_beh <- read.csv(paste0(getwd(), paste0('/data/allAverageDat_beh','.csv'))) # behavioral 
allAverageDat <- read.csv(paste0(getwd(), paste0('/data/allAverageDat','.csv'))) # cnv 
m_validAverageDat_short <- read.csv(paste0(getwd(), paste0('/data/allAverageDat_short','.csv'))) #cnv plot 
cnv_width_per <- read.csv(paste0(getwd(), paste0('/data/cnv_width_per','.csv'))) #cnv width perception
allAverageDat_p2 <- read.csv(paste0(getwd(), paste0('/data/allAverageDat_p2' ,'.csv'))) # offset-P2
allAverageDat_resp <- read.csv(paste0(getwd(), paste0('/data/allAverageDat_resp' ,'.csv'))) # response-locked LPCt
cnv_width_rep <- read.csv(paste0(getwd(), paste0('/data/cnv_width_rep','.csv'))) #cnv width reproduction