### This script calculates accuracy for each duration for Lukowska 2018
### Using rstanarm and leave one out cv (on a participant level)
setwd("/home/delpin/Documents/Work/SdtModel/DatafromOthers")
library("lme4")
library("rstanarm")
library("loo")
options(mc.cores = parallel::detectCores())

# Clear workspace
rm(list=ls())

# load data
data <- read.csv2("E1_gbr.csv")

# How many participants?
nrparticipants <- length(unique(data$id))

# Define null model
rtm0 <- stan_glmer(rt~+(1|id),
                 data=data, family=gaussian)

# Define model with one predictor
rtm1 <- update(rtm0,.~.+acc)

### Compare with classic loo
loo_rtm0 <- loo(rtm0)
loo_rtm1 <- loo(rtm1)
compare(loo_rtm0,loo_rtm1)

### Compare with grouped k-fold cv
kfold_split_stratified(K = nrparticipants, x = data$id)