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1255 lines
81 KiB
R
1255 lines
81 KiB
R
##############################################################################
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#----------------------------------------------------------------------------#
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################################## LIBRARIES #################################
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#----------------------------------------------------------------------------#
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##############################################################################
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library(TAM)
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library(doMC)
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library(parallel)
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library(pbmcapply)
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library(funprog)
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library(plyr)
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library(dplyr)
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library(readxl)
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lastChar <- function(str){
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substr(str, nchar(str), nchar(str))
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}
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source(paste0(getwd(),"/Scripts/Analysis/functions/resali.R"))
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##############################################################################
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#----------------------------------------------------------------------------#
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############################# ANALYSIS FUNCTIONS #############################
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#----------------------------------------------------------------------------#
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##############################################################################
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pcm_analysis <- function(df=NULL,treatment='TT',irtmodel='PCM2',method='MML') {
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nbitems <- sum(sapply(1:20,function(x) paste0('item',x)) %in% colnames(df))
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resp <- df[,sapply(seq(1,nbitems),function(x) paste0('item',x))]
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if (method=='MML') {
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tam1 <- tam.mml(resp=resp,Y=df[,treatment],irtmodel = irtmodel,est.variance = T,verbose=F)
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}
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if (method=='JML') {
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tam1 <- tam.jml(resp=resp,group=1+df[,treatment])
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}
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if (method!='MML' & method!='JML') {
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stop('Invalid method. Please choose among MML or JML')
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}
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return(tam1)
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}
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replicate_pcm_analysis_m4 <- function(df=NULL,treatment='TT',irtmodel='PCM2',method='MML',sequence='replication',eff.size=0,difsize=NA,nbdif=0) {
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nbitems <- sum(sapply(1:20,function(x) paste0('item',x)) %in% colnames(df))
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resp <- df[,sapply(seq(1,nbitems),function(x) paste0('item',x))]
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truebeta <- eff.size
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if (method=='MML') {
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n <- max(df[,sequence])
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print(n)
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tam1 <- lapply(seq(1,n),
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function(x) pcm_analysis(df=df[df[,sequence]==x,],treatment=treatment,irtmodel=irtmodel)
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)
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}
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listitems <- c(sapply(c('_1','_2','_3'),function(x) paste0(sapply(seq(1,nbitems),function(x) paste0('item',x)),x)))
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returndat <- data.frame(matrix(nrow=max(df[,sequence]),ncol=length(listitems)))
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colnames(returndat) <- listitems
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for (s in seq(1,max(df[,sequence]))) {
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for (k in seq(1,nbitems)) {
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returndat[s,paste0('item',k,'_1')] <- tam1[[s]]$item[k,'AXsi_.Cat1']
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returndat[s,paste0('item',k,'_2')] <- tam1[[s]]$item[k,'AXsi_.Cat2']-tam1[[s]]$item[k,'AXsi_.Cat1']
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returndat[s,paste0('item',k,'_3')] <- tam1[[s]]$item[k,'AXsi_.Cat3']-tam1[[s]]$item[k,'AXsi_.Cat2']
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}
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}
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returndat <- returndat[,sort_by(listitems, lastChar)]
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returndat$beta <- sapply(seq(1,max(df[,sequence])),function(k) tam1[[k]]$beta[2])
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returndat$se.beta <- 1.413612*sapply(seq(1,max(df[,sequence])),function(k) tam.se(tam1[[k]])$beta$se.Dim1[2] )
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returndat$low.ci.beta <- returndat$beta-1.96*returndat$se.beta
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returndat$high.ci.beta <- returndat$beta+1.96*returndat$se.beta
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returndat$true.value.in.ci <- 1*(truebeta>returndat$low.ci.beta & truebeta<returndat$high.ci.beta)
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returndat$h0.rejected <- 1*(0<returndat$low.ci.beta | 0>returndat$high.ci.beta)
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if (truebeta==0) {
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returndat$beta.same.sign.truebeta <- NA
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} else {
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returndat$beta.same.sign.truebeta <- 1*(sign(truebeta)==sign(returndat$beta))
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}
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returndat2 <- data.frame(J=rep(nbitems,max(df[,sequence])),
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M=1+max(df$item1),
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N=nrow(df[df$replication==1,])/2,
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eff.size=truebeta,
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dif.size= difsize,
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nb.dif= nbdif
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)
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returndat <- cbind(returndat2,returndat)
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return(returndat)
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}
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replicate_pcm_analysis_m2 <- function(df=NULL,treatment='TT',irtmodel='PCM2',method='MML',sequence='replication',eff.size=0,difsize=NA,nbdif=0) {
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truebeta <- eff.size
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nbitems <- sum(sapply(1:20,function(x) paste0('item',x)) %in% colnames(df))
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resp <- df[,sapply(seq(1,nbitems),function(x) paste0('item',x))]
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if (method=='MML') {
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n <- max(df[,sequence])
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print(n)
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tam1 <- lapply(seq(1,n),
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function(x) pcm_analysis(df=df[df[,sequence]==x,],treatment=treatment,irtmodel=irtmodel)
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)
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}
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listitems <- sapply(seq(1,nbitems),function(x) paste0('item',x))
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returndat <- data.frame(matrix(nrow=max(df[,sequence]),ncol=length(listitems)))
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colnames(returndat) <- listitems
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for (s in seq(1,max(df[,sequence]))) {
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for (k in seq(1,nbitems)) {
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returndat[s,paste0('item',k)] <- tam1[[s]]$xsi$xsi[k]
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}
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}
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returndat$beta <- sapply(seq(1,max(df[,sequence])),function(k) tam1[[k]]$beta[2])
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returndat$se.beta <- 1.413612*sapply(seq(1,max(df[,sequence])),function(k) tam.se(tam1[[k]])$beta$se.Dim1[2] )
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returndat$low.ci.beta <- returndat$beta-1.96*returndat$se.beta
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returndat$high.ci.beta <- returndat$beta+1.96*returndat$se.beta
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returndat$true.value.in.ci <- 1*(truebeta>returndat$low.ci.beta & truebeta<returndat$high.ci.beta)
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returndat$h0.rejected <- 1*(0<returndat$low.ci.beta | 0>returndat$high.ci.beta)
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if (truebeta==0) {
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returndat$beta.same.sign.truebeta <- NA
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} else {
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returndat$beta.same.sign.truebeta <- 1*(sign(truebeta)==sign(returndat$beta))
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}
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returndat2 <- data.frame(J=rep(nbitems,max(df[,sequence])),
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M=1+max(df$item1),
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N=nrow(df[df$replication==1,])/2,
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eff.size=truebeta,
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dif.size= difsize,
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nb.dif= nbdif
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)
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returndat <- cbind(returndat2,returndat)
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return(returndat)
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}
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replicate_pcm_analysis<- function(df=NULL,treatment='TT',irtmodel='PCM2',method='MML',sequence='replication',eff.size=0,difsize=NA,nbdif=0) {
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j <- max(df$item1)
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if(j==1) {
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return(replicate_pcm_analysis_m2(df=df,treatment=treatment,irtmodel=irtmodel,method=method,sequence=sequence,eff.size=eff.size,difsize=difsize,nbdif=nbdif))
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} else {
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return(replicate_pcm_analysis_m4(df=df,treatment=treatment,irtmodel=irtmodel,method=method,sequence=sequence,eff.size=eff.size,difsize=difsize,nbdif=nbdif))
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}
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}
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##############################################################################
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#----------------------------------------------------------------------------#
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################################# AGGREGATION ################################
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#----------------------------------------------------------------------------#
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##############################################################################
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#### Create data.frame
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results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
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results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
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results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
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results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
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results <- c(results,results2)
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results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
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sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
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)
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#### Compiler function
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compile_simulation <- function(scenario) {
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name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
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if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name<=4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N50/scenario_',scenario,'.csv'))
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}
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if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name>4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N50/scenario_',scenario,'.csv'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name<=4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N100/scenario_',scenario,'.csv'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N100/scenario_',scenario,'_nodif.csv'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name<=4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N200/scenario_',scenario,'.csv'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N200/scenario_',scenario,'_nodif.csv'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name<=4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N300/scenario_',scenario,'.csv'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>4) {
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s <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N300/scenario_',scenario,'_nodif.csv'))
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}
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if (unique(s$J)==4) {
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if (unique(s$M)==2) {
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a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4))
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} else {
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a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
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m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
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m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
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m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3)
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)
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}
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} else {
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if (unique(s$M)==2) {
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a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4),
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m.item5=mean(s$item5),m.item6=mean(s$item6),m.item7=mean(s$item7))
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} else {
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a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
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m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
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m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
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m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3),
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m.item5_1=mean(s$item5_1),m.item5_2=mean(s$item5_2),m.item5_3=mean(s$item5_3),
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m.item6_1=mean(s$item6_1),m.item6_2=mean(s$item6_2),m.item6_3=mean(s$item6_3),
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m.item7_1=mean(s$item7_1),m.item7_2=mean(s$item7_2),m.item7_3=mean(s$item7_3)
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)
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}
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}
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N <- ifelse(substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50","50",substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario)))
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zz <- ifelse(N=="50",substr(scenario,start=0,stop=nchar(scenario)-3),substr(scenario,start=0,stop=nchar(scenario)-4))
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b <- data.frame(scenario=zz,
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scenario.type=substr(zz,start=nchar(zz),stop=nchar(zz)),
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N=N,
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J=unique(s$J),
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M=unique(s$M),
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eff.size=unique(s$eff.size),
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nb.dif=unique(s$nb.dif),
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dif.size=unique(s$dif.size)
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)
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z <- data.frame(m.beta=mean(s$beta),
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se.empirical.beta=sd(s$beta),
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se.analytical.beta=mean(s$se.beta),
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m.low.ci.beta=mean(s$low.ci.beta),
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m.high.ci.beta=mean(s$high.ci.beta),
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true.value.in.ci.p=mean(s$true.value.in.ci),
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h0.rejected.p=mean(s$h0.rejected),
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beta.same.sign.truebeta.p=mean(s$beta.same.sign.truebeta,na.rm=T),
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beta.same.sign.truebeta.signif.p=mean(s[s$h0.rejected==1,]$beta.same.sign.truebeta,na.rm=T))
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d <- cbind(b,a,z)
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d$prop.
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return(d)
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}
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#### Compiled results
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res.dat <- compile_simulation('2A_50')
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for (x in results[seq(2,length(results))]) {
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y <- compile_simulation(x)
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res.dat <- bind_rows(res.dat,y)
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}
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res.dat[res.dat$scenario.type=='A','dif.size'] <- -res.dat[res.dat$scenario.type=='A','dif.size']
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res.dat[is.na(res.dat$dif.size),'dif.size'] <- 0
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res.dat[res.dat$scenario=="10B",]$dif.size <- 0.3
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res.dat[substr(res.dat$scenario,1,1)%in%c("6","8"),'nb.dif'] <- 1
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res.dat[substr(res.dat$scenario,1,2)%in%seq(10,16,2),'nb.dif'] <- 2
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res.dat[substr(res.dat$scenario,1,2)%in%seq(18,20,2),'nb.dif'] <- 3
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res.dat[res.dat$N==50,"dif.size"] <- res.dat[which(res.dat$N==50)+1,"dif.size"]
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res.dat[res.dat$scenario.type=="B",]$eff.size <- 0.2
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res.dat[res.dat$scenario.type=="C" & res.dat$dif.size==0,]$eff.size <- 0.4
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res.dat[res.dat$scenario.type=="C" & res.dat$dif.size!=0,]$eff.size <- 0.2
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res.dat[res.dat$scenario.type=="D" & res.dat$dif.size!=0,]$eff.size <- 0.4
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res.dat[res.dat$scenario.type=="E" & res.dat$dif.size!=0,]$eff.size <- 0.4
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is.nan.data.frame <- function(x) {
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do.call(cbind, lapply(x, is.nan))
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}
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res.dat[is.nan(res.dat)] <- NA
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res.dat$bias <- res.dat$eff.size-res.dat$m.beta
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##############################################################################
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#----------------------------------------------------------------------------#
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########################### AGGREGATION DIF MATRICES #########################
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#----------------------------------------------------------------------------#
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##############################################################################
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#### Create data.frame
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results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
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results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
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results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
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results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
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results <- c(results,results2)
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results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
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sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
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)
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results <- results[19:length(results)]
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#### Compiler function
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compile_simulation2 <- function(scenario) {
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name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
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if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name>4) {
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s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N50/',scenario,'.xls'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>4) {
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s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N100/',scenario,'.xls'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>4) {
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s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N200/',scenario,'.xls'))
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}
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if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>4) {
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s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N300/',scenario,'.xls'))
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}
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J <- max(which(sapply(1:7,function(x) paste0('item',x) %in% colnames(s) | paste0('item',x,'_1') %in% colnames(s))))
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M <- 1+sum(sapply(1:3,function(x) paste0('item1_',x) %in% colnames(s) ))
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if (M==1) {M <- 2}
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nb.dif <- max(which(sapply(1:3,function(x) paste0('dif',x) %in% colnames(s) | paste0('dif',x,'_1') %in% colnames(s))))
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if (J==4) {
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if (M==2) {
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a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4))
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} else {
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a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
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m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
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|
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
|
|
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3)
|
|
)
|
|
}
|
|
} else {
|
|
if (M==2) {
|
|
a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4),
|
|
m.item5=mean(s$item5),m.item6=mean(s$item6),m.item7=mean(s$item7))
|
|
} else {
|
|
a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
|
|
m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
|
|
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
|
|
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3),
|
|
m.item5_1=mean(s$item5_1),m.item5_2=mean(s$item5_2),m.item5_3=mean(s$item5_3),
|
|
m.item6_1=mean(s$item6_1),m.item6_2=mean(s$item6_2),m.item6_3=mean(s$item6_3),
|
|
m.item7_1=mean(s$item7_1),m.item7_2=mean(s$item7_2),m.item7_3=mean(s$item7_3)
|
|
)
|
|
}
|
|
}
|
|
N <- ifelse(substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50","50",substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario)))
|
|
zz <- ifelse(N=="50",substr(scenario,start=0,stop=nchar(scenario)-3),substr(scenario,start=0,stop=nchar(scenario)-4))
|
|
eff.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'eff.size'])
|
|
dif.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'dif.size'])
|
|
b <- data.frame(scenario=zz,
|
|
scenario.type=substr(zz,start=nchar(zz),stop=nchar(zz)),
|
|
N=N,
|
|
J=J,
|
|
M=M,
|
|
eff.size=eff.size,
|
|
nb.dif=nb.dif,
|
|
dif.size=dif.size
|
|
)
|
|
true.value.in.ci <- eff.size <= s$beta+1.96*s$se_beta & eff.size >= s$beta-1.96*s$se_beta
|
|
beta.same.sign.truebeta.p <- ifelse(rep(eff.size,nrow(s))==0,NA,(rep(eff.size,nrow(s))/s$beta)>0)
|
|
num.reject <- which((s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0)
|
|
z <- data.frame(m.beta=mean(s$beta),
|
|
se.empirical.beta=sd(s$beta),
|
|
se.analytical.beta=mean(s$se_beta),
|
|
m.low.ci.beta=mean(s$beta-1.96*s$se_beta),
|
|
m.high.ci.beta=mean(s$beta+1.96*s$se_beta),
|
|
true.value.in.ci.p=mean(true.value.in.ci),
|
|
h0.rejected.p=mean( (s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0 ),
|
|
beta.same.sign.truebeta.p=mean(beta.same.sign.truebeta.p),
|
|
beta.same.sign.truebeta.signif.p=mean(beta.same.sign.truebeta.p[num.reject])
|
|
)
|
|
d <- cbind(b,a,z)
|
|
d$prop.
|
|
return(d)
|
|
}
|
|
|
|
|
|
#### Compiled results
|
|
|
|
res.dat.dif <- compile_simulation2('6A_50')
|
|
|
|
for (x in results[seq(2,length(results))]) {
|
|
y <- compile_simulation2(x)
|
|
res.dat.dif <- bind_rows(res.dat.dif,y)
|
|
}
|
|
|
|
res.dat.dif[is.na(res.dat.dif$dif.size),'dif.size'] <- 0
|
|
res.dat.dif[substr(res.dat.dif$scenario,1,1)%in%c("6","8"),'nb.dif'] <- 1
|
|
res.dat.dif[substr(res.dat.dif$scenario,1,2)%in%seq(10,16,2),'nb.dif'] <- 2
|
|
res.dat.dif[substr(res.dat.dif$scenario,1,2)%in%seq(18,20,2),'nb.dif'] <- 3
|
|
res.dat.dif[res.dat.dif$N==50,"dif.size"] <- res.dat.dif[which(res.dat.dif$N==50)+1,"dif.size"]
|
|
res.dat.dif[res.dat.dif$scenario.type=="B",]$eff.size <- 0.2
|
|
res.dat.dif[res.dat.dif$scenario.type=="C" & res.dat.dif$dif.size!=0,]$eff.size <- 0.2
|
|
res.dat.dif[res.dat.dif$scenario.type=="D" & res.dat.dif$dif.size!=0,]$eff.size <- 0.4
|
|
res.dat.dif[res.dat.dif$scenario.type=="E" & res.dat.dif$dif.size!=0,]$eff.size <- 0.4
|
|
res.dat.dif[res.dat.dif$scenario=="10B",]$dif.size <- 0.3
|
|
res.dat.dif$bias <- res.dat.dif$eff.size-res.dat.dif$m.beta
|
|
|
|
##############################################################################
|
|
#----------------------------------------------------------------------------#
|
|
####################### AGGREGATION DIF MATRICES ROSALI ######################
|
|
#----------------------------------------------------------------------------#
|
|
##############################################################################
|
|
|
|
#### Create data.frame
|
|
|
|
results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
|
|
|
|
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
|
|
|
|
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
|
|
|
|
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
|
|
|
|
results <- c(results,results2)
|
|
|
|
results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
|
|
sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
|
|
)
|
|
|
|
#### Compiler function
|
|
|
|
compile_simulation2_rosali <- function(scenario) {
|
|
name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
|
|
if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N50/',scenario,'_original.xls'))
|
|
}
|
|
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N100/',scenario,'_original.xls'))
|
|
}
|
|
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N200/',scenario,'_original.xls'))
|
|
}
|
|
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N300/',scenario,'_original.xls'))
|
|
}
|
|
J <- max(which(sapply(1:7,function(x) paste0('item',x) %in% colnames(s) | paste0('item',x,'_1') %in% colnames(s))))
|
|
M <- 1+sum(sapply(1:3,function(x) paste0('item1_',x) %in% colnames(s) ))
|
|
if (M==1) {M <- 2}
|
|
nb.dif.true <- ifelse(name<=4,0,ifelse(name<=8,1,ifelse(name<=16,2,3)))
|
|
if (name %in% c(3,4,13:20)) {
|
|
m.nb.dif.detect <- mean(ifelse(is.na(s$dif_1_1),0,
|
|
ifelse(is.na(s$dif_2_1),1,
|
|
ifelse(is.na(s$dif_3_1),2,
|
|
ifelse(is.na(s$dif_4_1),3,
|
|
ifelse(is.na(s$dif_5_1),4,
|
|
ifelse(is.na(s$dif_6_1),5,
|
|
ifelse(is.na(s$dif_7_1),6,7))))))))
|
|
}
|
|
if (!(name %in% c(3,4,13:20))) {
|
|
m.nb.dif.detect <- mean(ifelse(is.na(s$dif_1_1),0,
|
|
ifelse(is.na(s$dif_2_1),1,
|
|
ifelse(is.na(s$dif_3_1),2,
|
|
ifelse(is.na(s$dif_4_1),3,4)))))
|
|
}
|
|
if (J==4) {
|
|
if (M==2) {
|
|
a <- data.frame(m.item1=mean(s$item1_1),m.item2=mean(s$item2_1),m.item3=mean(s$item3_1),m.item4=mean(s$item4_1))
|
|
} else {
|
|
a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
|
|
m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
|
|
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
|
|
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3)
|
|
)
|
|
}
|
|
} else {
|
|
if (M==2) {
|
|
a <- data.frame(m.item1=mean(s$item1_1),m.item2=mean(s$item2_1),m.item3=mean(s$item3_1),m.item4=mean(s$item4_1),
|
|
m.item5=mean(s$item5_1),m.item6=mean(s$item6_1),m.item7=mean(s$item7_1))
|
|
} else {
|
|
a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
|
|
m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
|
|
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
|
|
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3),
|
|
m.item5_1=mean(s$item5_1),m.item5_2=mean(s$item5_2),m.item5_3=mean(s$item5_3),
|
|
m.item6_1=mean(s$item6_1),m.item6_2=mean(s$item6_2),m.item6_3=mean(s$item6_3),
|
|
m.item7_1=mean(s$item7_1),m.item7_2=mean(s$item7_2),m.item7_3=mean(s$item7_3)
|
|
)
|
|
}
|
|
}
|
|
N <- ifelse(substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50","50",substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario)))
|
|
zz <- ifelse(N=="50",substr(scenario,start=0,stop=nchar(scenario)-3),substr(scenario,start=0,stop=nchar(scenario)-4))
|
|
eff.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'eff.size'])
|
|
dif.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'dif.size'])
|
|
b <- data.frame(scenario=zz,
|
|
scenario.type=substr(zz,start=nchar(zz),stop=nchar(zz)),
|
|
N=N,
|
|
J=J,
|
|
M=M,
|
|
eff.size=eff.size,
|
|
nb.dif=nb.dif.true,
|
|
m.nb.dif.detect=m.nb.dif.detect,
|
|
dif.size=dif.size
|
|
)
|
|
true.value.in.ci <- eff.size <= s$beta+1.96*s$se_beta & eff.size >= s$beta-1.96*s$se_beta
|
|
beta.same.sign.truebeta.p <- ifelse(rep(eff.size,nrow(s))==0,NA,(rep(eff.size,nrow(s))/s$beta)>0)
|
|
num.reject <- which((s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0)
|
|
dif.d <- mean(sapply(1:1000,function(x) any(!is.na(s[x,paste0("dif_",1:unique(b$J),"_1")]))))
|
|
if (nb.dif.true==0 & unique(b$J)==4) {
|
|
prop.perfect <- NA
|
|
flexible.detect <- NA
|
|
moreflexible.detect <- NA
|
|
any.detect <- NA
|
|
thay.tpr <- NA
|
|
thay.fpr <- mean(sapply(1:1000,function(x) sum( !is.na(s[x,paste0("dif_detect_",1:4)]) )/4 ))
|
|
}
|
|
if (nb.dif.true==0 & unique(b$J)==7) {
|
|
prop.perfect <- NA
|
|
flexible.detect <- NA
|
|
moreflexible.detect <- NA
|
|
any.detect <- NA
|
|
thay.tpr <- NA
|
|
thay.fpr <- mean(sapply(1:1000,function(x) sum( !is.na(s[x,paste0("dif_detect_",1:7)]) )/7 ))
|
|
}
|
|
if (nb.dif.true==1 & unique(b$J)==4 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1,s[x,"dif_detect_unif_1"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- moreflexible.detect
|
|
thay.tpr <- moreflexible.detect
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])!=s[x,"real_dif_1"],na.rm=F)/4,0) ))
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==4 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/4,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==7 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==3 & unique(b$J)==7 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,"dif_detect_unif_3"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) & s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) | s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"]),na.rm=F)/3,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==1 & unique(b$J)==4 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1, s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- moreflexible.detect
|
|
thay.tpr <- moreflexible.detect
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])!=s[x,"real_dif_1"],na.rm=F)/4,0) ))
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==4 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/4,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==7 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==3 & unique(b$J)==7 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) & s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) | s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"]),na.rm=F)/3,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
lrt.pass <- mean(s$lrt_passed)
|
|
z <- data.frame(m.beta=mean(s$beta),
|
|
se.empirical.beta=sd(s$beta),
|
|
se.analytical.beta=mean(s$se_beta),
|
|
m.low.ci.beta=mean(s$beta-1.96*s$se_beta),
|
|
m.high.ci.beta=mean(s$beta+1.96*s$se_beta),
|
|
true.value.in.ci.p=mean(true.value.in.ci),
|
|
h0.rejected.p=mean( (s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0 ),
|
|
beta.same.sign.truebeta.p=mean(beta.same.sign.truebeta.p),
|
|
beta.same.sign.truebeta.signif.p=mean(beta.same.sign.truebeta.p[num.reject]),
|
|
dif.detected=dif.d,
|
|
prop.perfect=prop.perfect,
|
|
flexible.detect=flexible.detect,
|
|
moreflexible.detect=moreflexible.detect,
|
|
any.detect=any.detect,
|
|
thay.tpr=thay.tpr,
|
|
thay.fpr=thay.fpr,
|
|
lrt.pass=lrt.pass
|
|
)
|
|
d <- cbind(b,a,z)
|
|
d$prop.
|
|
return(d)
|
|
}
|
|
|
|
|
|
#### Compiled results
|
|
|
|
res.dat.dif.rosali <- compile_simulation2_rosali('2A_50')
|
|
|
|
for (x in results[seq(2,length(results))]) {
|
|
y <- compile_simulation2_rosali(x)
|
|
res.dat.dif.rosali <- bind_rows(res.dat.dif.rosali,y)
|
|
}
|
|
|
|
res.dat.dif.rosali[res.dat.dif.rosali$scenario.type=='A','dif.size'] <- -res.dat.dif.rosali[res.dat.dif.rosali$scenario.type=='A','dif.size']
|
|
res.dat.dif.rosali[is.na(res.dat.dif.rosali$dif.size),'dif.size'] <- 0
|
|
res.dat.dif.rosali[substr(res.dat.dif.rosali$scenario,1,1)%in%c("6","8"),'nb.dif'] <- 1
|
|
res.dat.dif.rosali[substr(res.dat.dif.rosali$scenario,1,2)%in%seq(10,16,2),'nb.dif'] <- 2
|
|
res.dat.dif.rosali[substr(res.dat.dif.rosali$scenario,1,2)%in%seq(18,20,2),'nb.dif'] <- 3
|
|
res.dat.dif.rosali[res.dat.dif.rosali$N==50,"dif.size"] <- res.dat.dif.rosali[which(res.dat.dif.rosali$N==50)+1,"dif.size"]
|
|
res.dat.dif.rosali[res.dat.dif.rosali$scenario.type=="B",]$eff.size <- 0.2
|
|
res.dat.dif.rosali[res.dat.dif.rosali$scenario.type=="C" & res.dat.dif.rosali$dif.size==0,]$eff.size <- 0.4
|
|
res.dat.dif.rosali[res.dat.dif.rosali$scenario.type=="C" & res.dat.dif.rosali$dif.size!=0,]$eff.size <- 0.2
|
|
res.dat.dif.rosali[res.dat.dif.rosali$scenario.type=="D" & res.dat.dif.rosali$dif.size!=0,]$eff.size <- 0.4
|
|
res.dat.dif.rosali[res.dat.dif.rosali$scenario.type=="E" & res.dat.dif.rosali$dif.size!=0,]$eff.size <- 0.4
|
|
res.dat.dif.rosali[res.dat.dif.rosali$scenario=="10B",]$dif.size <- 0.3
|
|
|
|
is.nan.data.frame <- function(x) {
|
|
do.call(cbind, lapply(x, is.nan))
|
|
}
|
|
|
|
|
|
res.dat.dif.rosali[is.nan(res.dat.dif.rosali)] <- NA
|
|
|
|
res.dat.dif.rosali$bias <- res.dat.dif.rosali$eff.size-res.dat.dif.rosali$m.beta
|
|
|
|
|
|
##############################################################################
|
|
#----------------------------------------------------------------------------#
|
|
####################### AGGREGATION DIF MATRICES RESALI ######################
|
|
#----------------------------------------------------------------------------#
|
|
##############################################################################
|
|
|
|
#### Create data.frame
|
|
|
|
|
|
results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
|
|
|
|
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
|
|
|
|
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
|
|
|
|
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
|
|
|
|
results <- c(results,results2)
|
|
|
|
results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
|
|
sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
|
|
)
|
|
|
|
|
|
#### Compiler function
|
|
|
|
compile_simulation2_resali <- function(scenario) {
|
|
name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
|
|
if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N50/',scenario,'_original.xls'))
|
|
}
|
|
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N100/',scenario,'_original.xls'))
|
|
}
|
|
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N200/',scenario,'_original.xls'))
|
|
}
|
|
if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>0) {
|
|
s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N300/',scenario,'_original.xls'))
|
|
}
|
|
J <- max(which(sapply(1:7,function(x) paste0('item',x) %in% colnames(s) | paste0('item',x,'_1') %in% colnames(s))))
|
|
M <- 1+sum(sapply(1:3,function(x) paste0('item1_',x) %in% colnames(s) ))
|
|
if (M==1) {M <- 2}
|
|
nb.dif.true <- ifelse(name<=4,0,ifelse(name<=8,1,ifelse(name<=16,2,3)))
|
|
if (name %in% c(3,4,13:20)) {
|
|
m.nb.dif.detect <- mean(ifelse(is.na(s$dif_1_1),0,
|
|
ifelse(is.na(s$dif_2_1),1,
|
|
ifelse(is.na(s$dif_3_1),2,
|
|
ifelse(is.na(s$dif_4_1),3,
|
|
ifelse(is.na(s$dif_5_1),4,
|
|
ifelse(is.na(s$dif_6_1),5,
|
|
ifelse(is.na(s$dif_7_1),6,7))))))))
|
|
}
|
|
if (!(name %in% c(3,4,13:20))) {
|
|
m.nb.dif.detect <- mean(ifelse(is.na(s$dif_1_1),0,
|
|
ifelse(is.na(s$dif_2_1),1,
|
|
ifelse(is.na(s$dif_3_1),2,
|
|
ifelse(is.na(s$dif_4_1),3,4)))))
|
|
}
|
|
if (J==4) {
|
|
if (M==2) {
|
|
a <- data.frame(m.item1=mean(s$item1_1),m.item2=mean(s$item2_1),m.item3=mean(s$item3_1),m.item4=mean(s$item4_1))
|
|
} else {
|
|
a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
|
|
m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
|
|
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
|
|
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3)
|
|
)
|
|
}
|
|
} else {
|
|
if (M==2) {
|
|
a <- data.frame(m.item1=mean(s$item1_1),m.item2=mean(s$item2_1),m.item3=mean(s$item3_1),m.item4=mean(s$item4_1),
|
|
m.item5=mean(s$item5_1),m.item6=mean(s$item6_1),m.item7=mean(s$item7_1))
|
|
} else {
|
|
a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
|
|
m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
|
|
m.item3_1=mean(s$item3_1),m.item3_2=mean(s$item3_2),m.item3_3=mean(s$item3_3),
|
|
m.item4_1=mean(s$item4_1),m.item4_2=mean(s$item4_2),m.item4_3=mean(s$item4_3),
|
|
m.item5_1=mean(s$item5_1),m.item5_2=mean(s$item5_2),m.item5_3=mean(s$item5_3),
|
|
m.item6_1=mean(s$item6_1),m.item6_2=mean(s$item6_2),m.item6_3=mean(s$item6_3),
|
|
m.item7_1=mean(s$item7_1),m.item7_2=mean(s$item7_2),m.item7_3=mean(s$item7_3)
|
|
)
|
|
}
|
|
}
|
|
N <- ifelse(substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50","50",substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario)))
|
|
zz <- ifelse(N=="50",substr(scenario,start=0,stop=nchar(scenario)-3),substr(scenario,start=0,stop=nchar(scenario)-4))
|
|
eff.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'eff.size'])
|
|
dif.size <- unique(res.dat[res.dat$scenario==zz & res.dat$N==N,'dif.size'])
|
|
b <- data.frame(scenario=zz,
|
|
scenario.type=substr(zz,start=nchar(zz),stop=nchar(zz)),
|
|
N=N,
|
|
J=J,
|
|
M=M,
|
|
eff.size=eff.size,
|
|
nb.dif=nb.dif.true,
|
|
m.nb.dif.detect=m.nb.dif.detect,
|
|
dif.size=dif.size
|
|
)
|
|
true.value.in.ci <- eff.size <= s$beta+1.96*s$se_beta & eff.size >= s$beta-1.96*s$se_beta
|
|
beta.same.sign.truebeta.p <- ifelse(rep(eff.size,nrow(s))==0,NA,(rep(eff.size,nrow(s))/s$beta)>0)
|
|
num.reject <- which((s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0)
|
|
dif.d <- mean(sapply(1:1000,function(x) any(!is.na(s[x,paste0("dif_",1:unique(b$J),"_1")]))))
|
|
if (nb.dif.true==0 & unique(b$J)==4) {
|
|
prop.perfect <- NA
|
|
flexible.detect <- NA
|
|
moreflexible.detect <- NA
|
|
any.detect <- NA
|
|
thay.tpr <- NA
|
|
thay.fpr <- mean(sapply(1:1000,function(x) sum( !is.na(s[x,paste0("dif_detect_",1:4)]) )/4 ))
|
|
}
|
|
if (nb.dif.true==0 & unique(b$J)==7) {
|
|
prop.perfect <- NA
|
|
flexible.detect <- NA
|
|
moreflexible.detect <- NA
|
|
any.detect <- NA
|
|
thay.tpr <- NA
|
|
thay.fpr <- mean(sapply(1:1000,function(x) sum( !is.na(s[x,paste0("dif_detect_",1:7)]) )/7 ))
|
|
}
|
|
if (nb.dif.true==1 & unique(b$J)==4 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1,s[x,"dif_detect_unif_1"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- moreflexible.detect
|
|
thay.tpr <- moreflexible.detect
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])!=s[x,"real_dif_1"],na.rm=F)/4,0) ))
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==4 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/4,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==7 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==3 & unique(b$J)==7 & unique(b$M)==4) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,"dif_detect_unif_3"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")])
|
|
,0) )
|
|
flexible.detect <- mean(flexible.detect)
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) & s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) | s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"]),na.rm=F)/3,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==1 & unique(b$J)==4 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1, s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- moreflexible.detect
|
|
thay.tpr <- moreflexible.detect
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])!=s[x,"real_dif_1"],na.rm=F)/4,0) ))
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==4 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:4)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/4,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==2 & unique(b$J)==7 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"]),na.rm=F)/2,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
if (nb.dif.true==3 & unique(b$J)==7 & unique(b$M)==2) {
|
|
perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")])
|
|
,0) )
|
|
prop.perfect <- mean(perfect.detection)
|
|
flexible.detect <- prop.perfect
|
|
moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) & s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
moreflexible.detect <- mean(moreflexible.detect)
|
|
any.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) |
|
|
s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) | s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
|
|
any.detect <- mean(any.detect)
|
|
thay.tpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"]),na.rm=F)/3,0) ))
|
|
thay.fpr <- mean(sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,sum(!(unlist(s[x,paste0("dif_detect_",1:7)])%in%c(s[x,"real_dif_1"],s[x,"real_dif_2"],s[x,"real_dif_3"])),na.rm=F)/7,0) ))
|
|
|
|
}
|
|
z <- data.frame(m.beta=mean(s$beta),
|
|
se.empirical.beta=sd(s$beta),
|
|
se.analytical.beta=mean(s$se_beta),
|
|
m.low.ci.beta=mean(s$beta-1.96*s$se_beta),
|
|
m.high.ci.beta=mean(s$beta+1.96*s$se_beta),
|
|
true.value.in.ci.p=mean(true.value.in.ci),
|
|
h0.rejected.p=mean( (s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0 ),
|
|
beta.same.sign.truebeta.p=mean(beta.same.sign.truebeta.p),
|
|
beta.same.sign.truebeta.signif.p=mean(beta.same.sign.truebeta.p[num.reject]),
|
|
dif.detected=dif.d,
|
|
prop.perfect=prop.perfect,
|
|
flexible.detect=flexible.detect,
|
|
moreflexible.detect=moreflexible.detect,
|
|
any.detect=any.detect
|
|
)
|
|
d <- cbind(b,a,z)
|
|
d$prop.
|
|
return(d)
|
|
}
|
|
|
|
|
|
#### Compiled results
|
|
|
|
res.dat.dif.resali <- compile_simulation2_resali('2A_50')
|
|
|
|
for (x in results[seq(2,length(results))]) {
|
|
y <- compile_simulation2_resali(x)
|
|
res.dat.dif.resali <- bind_rows(res.dat.dif.resali,y)
|
|
}
|
|
|
|
res.dat.dif.resali[res.dat.dif.resali$scenario.type=='A','dif.size'] <- -res.dat.dif.resali[res.dat.dif.resali$scenario.type=='A','dif.size']
|
|
res.dat.dif.resali[is.na(res.dat.dif.resali$dif.size),'dif.size'] <- 0
|
|
res.dat.dif.resali[substr(res.dat.dif.resali$scenario,1,1)%in%c("6","8"),'nb.dif'] <- 1
|
|
res.dat.dif.resali[substr(res.dat.dif.resali$scenario,1,2)%in%seq(10,16,2),'nb.dif'] <- 2
|
|
res.dat.dif.resali[substr(res.dat.dif.resali$scenario,1,2)%in%seq(18,20,2),'nb.dif'] <- 3
|
|
res.dat.dif.resali[res.dat.dif.resali$N==50,"dif.size"] <- res.dat.dif.resali[which(res.dat.dif.resali$N==50)+1,"dif.size"]
|
|
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="B",]$eff.size <- 0.2
|
|
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="C" & res.dat.dif.resali$dif.size==0,]$eff.size <- 0.4
|
|
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="C" & res.dat.dif.resali$dif.size!=0,]$eff.size <- 0.2
|
|
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="D" & res.dat.dif.resali$dif.size!=0,]$eff.size <- 0.4
|
|
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="E" & res.dat.dif.resali$dif.size!=0,]$eff.size <- 0.4
|
|
res.dat.dif.resali[res.dat.dif.resali$scenario=="10B",]$dif.size <- 0.3
|
|
|
|
is.nan.data.frame <- function(x) {
|
|
do.call(cbind, lapply(x, is.nan))
|
|
}
|
|
|
|
|
|
res.dat.dif.resali[is.nan(res.dat.dif.resali)] <- NA
|
|
|
|
res.dat.dif.resali$bias <- res.dat.dif.resali$eff.size-res.dat.dif.resali$m.beta
|
|
|
|
|
|
|
|
##############################################################################
|
|
#----------------------------------------------------------------------------#
|
|
################################## RASCHPOWER ################################
|
|
#----------------------------------------------------------------------------#
|
|
##############################################################################
|
|
|
|
###### Puissance théorique
|
|
|
|
res.dat$theoretical.power <- 0
|
|
|
|
### Scénarios N=100
|
|
|
|
## Scénarios J=4 / M=4
|
|
|
|
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'A') & res.dat$N==100,]$theoretical.power <- 0.05
|
|
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'B') & res.dat$N==100,]$theoretical.power <- 0.2177
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'C') & res.dat$N==100,]$theoretical.power <- 0.2177
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'D') & res.dat$N==100,]$theoretical.power <- 0.6586
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'E') & res.dat$N==100,]$theoretical.power <- 0.6586
|
|
|
|
res.dat[res.dat$scenario %in% paste0(2,'C') & res.dat$N==100,]$theoretical.power <- 0.6586
|
|
|
|
## Scénarios J=7 / M=4
|
|
|
|
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'A') & res.dat$N==100,]$theoretical.power <- 0.05
|
|
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'B') & res.dat$N==100,]$theoretical.power <- 0.2450
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'C') & res.dat$N==100,]$theoretical.power <- 0.2450
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'D') & res.dat$N==100,]$theoretical.power <- 0.7136
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'E') & res.dat$N==100,]$theoretical.power <- 0.7136
|
|
|
|
res.dat[res.dat$scenario %in% paste0(4,'C') & res.dat$N==100,]$theoretical.power <- 0.7136
|
|
|
|
|
|
|
|
### Scénarios N=300
|
|
|
|
## Scénarios J=4 / M=4
|
|
|
|
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'A') & res.dat$N==300,]$theoretical.power <- 0.05
|
|
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'B') & res.dat$N==300,]$theoretical.power <- 0.5373
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'C') & res.dat$N==300,]$theoretical.power <- 0.5373
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'D') & res.dat$N==300,]$theoretical.power <- 0.9834
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'E') & res.dat$N==300,]$theoretical.power <- 0.9834
|
|
|
|
res.dat[res.dat$scenario %in% paste0(2,'C') & res.dat$N==300,]$theoretical.power <- 0.9834
|
|
|
|
## Scénarios J=7 / M=4
|
|
|
|
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'A') & res.dat$N==300,]$theoretical.power <- 0.05
|
|
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'B') & res.dat$N==300,]$theoretical.power <- 0.5907
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'C') & res.dat$N==300,]$theoretical.power <- 0.5907
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'D') & res.dat$N==300,]$theoretical.power <- 0.9919
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'E') & res.dat$N==300,]$theoretical.power <- 0.9919
|
|
|
|
res.dat[res.dat$scenario %in% paste0(4,'C') & res.dat$N==300,]$theoretical.power <- 0.9919
|
|
|
|
|
|
### Scénarios N=50
|
|
|
|
## Scénarios J=4 / M=4
|
|
|
|
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'A') & res.dat$N==50,]$theoretical.power <- 0.05
|
|
res.dat[res.dat$scenario %in% paste0(c(2,6,8,10,12),'B') & res.dat$N==50,]$theoretical.power <- 0.1339
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'C') & res.dat$N==50,]$theoretical.power <- 0.1339
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'D') & res.dat$N==50,]$theoretical.power <- 0.3863
|
|
res.dat[res.dat$scenario %in% paste0(c(6,8,10,12),'E') & res.dat$N==50,]$theoretical.power <- 0.3863
|
|
|
|
res.dat[res.dat$scenario %in% paste0(2,'C') & res.dat$N==50,]$theoretical.power <- 0.3863
|
|
|
|
## Scénarios J=7 / M=4
|
|
|
|
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'A') & res.dat$N==50,]$theoretical.power <- 0.05
|
|
res.dat[res.dat$scenario %in% paste0(c(4,14,16,18,20),'B') & res.dat$N==50,]$theoretical.power <- 0.1448
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'C') & res.dat$N==50,]$theoretical.power <- 0.1448
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'D') & res.dat$N==50,]$theoretical.power <- 0.4328
|
|
res.dat[res.dat$scenario %in% paste0(c(14,16,18,20),'E') & res.dat$N==50,]$theoretical.power <- 0.4328
|
|
|
|
res.dat[res.dat$scenario %in% paste0(4,'C') & res.dat$N==50,]$theoretical.power <- 0.4328
|
|
|
|
### DIF scenarios
|
|
|
|
res.dat.dif$theoretical.power <- res.dat[res.dat$dif.size!=0,]$theoretical.power
|
|
res.dat.dif.rosali$theoretical.power <- res.dat$theoretical.power
|
|
res.dat.dif.resali$theoretical.power <- res.dat$theoretical.power
|
|
|
|
|
|
##############################################################################
|
|
#----------------------------------------------------------------------------#
|
|
######################### AGGREGATION OF ALL METHODS #########################
|
|
#----------------------------------------------------------------------------#
|
|
##############################################################################
|
|
|
|
# Items dichotomiques
|
|
|
|
res.dat$method <- "NONE"
|
|
res.dat.dif$method <- "PERFECT"
|
|
res.dat.dif.rosali$method <- "ROSALI"
|
|
res.dat.dif.resali$method <- "RESIDUS"
|
|
|
|
|
|
# Items polytomiques
|
|
|
|
res.dat.full <- res.dat[res.dat$M==4,]
|
|
res.dat.full <- rbind(res.dat.full,res.dat.dif[res.dat.dif$M==4,])
|
|
res.dat.full <- rbind.fill(res.dat.full,res.dat.dif.rosali[res.dat.dif.rosali$M==4,])
|
|
res.dat.full <- rbind.fill(res.dat.full,res.dat.dif.resali[res.dat.dif.resali$M==4,])
|
|
|
|
##############################################################################
|
|
#----------------------------------------------------------------------------#
|
|
############################ ARTICLE TABLE OUTPUT ############################
|
|
#----------------------------------------------------------------------------#
|
|
##############################################################################
|
|
|
|
# STRATEGY 1 - IGNORE DIF
|
|
|
|
res.dat.article <- res.dat[,c("N","J","eff.size","nb.dif","dif.size",
|
|
"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
|
|
"theoretical.power")]
|
|
colnames(res.dat.article)[3] <- "true.beta"
|
|
colnames(res.dat.article)[5] <- "true.gamma"
|
|
colnames(res.dat.article)[6] <- "betahat"
|
|
colnames(res.dat.article)[8] <- "coverage"
|
|
colnames(res.dat.article)[9] <- "power"
|
|
res.dat.article[,6:10] <- round(res.dat.article[,6:10],2)
|
|
res.dat.article[res.dat.article$true.beta==0,"typeIerror"] <- res.dat.article[res.dat.article$true.beta==0,"power"]
|
|
res.dat.article[res.dat.article$true.beta==0,"power"] <- NA
|
|
res.dat.article <- res.dat.article[,c(1:7,11,9:10,8)]
|
|
res.dat.article[res.dat.article$nb.dif==0,"true.gamma"] <- NA
|
|
res.dat.article[is.na(res.dat.article)] <- " "
|
|
res.dat.article$bias <- -1*res.dat.article$bias
|
|
res.dat.article.ignore <- reshape(res.dat.article[res.dat.article$nb.dif>0,],
|
|
direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N" )
|
|
write.csv(res.dat.article.ignore,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_ignoreDIF.csv")
|
|
res.dat.article.nodif.long <- res.dat.article[res.dat.article$nb.dif==0,]
|
|
res.dat.article.nodif <- reshape(res.dat.article[res.dat.article$nb.dif==0,],
|
|
direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N" )
|
|
write.csv(res.dat.article.nodif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_noDIF.csv")
|
|
res.dat.article <- reshape(res.dat.article[res.dat.article$nb.dif==0,],
|
|
direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N" )
|
|
write.csv(res.dat.article.nodif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_noDIF.csv")
|
|
|
|
|
|
|
|
res.dat.article.2 <- res.dat[,c("N","J","eff.size","nb.dif","dif.size",
|
|
"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
|
|
"theoretical.power")]
|
|
colnames(res.dat.article.2)[3] <- "true.beta"
|
|
colnames(res.dat.article.2)[5] <- "true.gamma"
|
|
colnames(res.dat.article.2)[6] <- "betahat"
|
|
colnames(res.dat.article.2)[8] <- "coverage"
|
|
colnames(res.dat.article.2)[9] <- "power"
|
|
res.dat.article.2[,6:10] <- round(res.dat.article.2[,6:10],2)
|
|
res.dat.article.2[res.dat.article.2$true.beta==0,"typeIerror"] <- res.dat.article.2[res.dat.article.2$true.beta==0,"power"]
|
|
res.dat.article.2[res.dat.article.2$true.beta==0,"power"] <- NA
|
|
res.dat.article.2 <- res.dat.article.2[,c(1:7,11,9:10,8)]
|
|
res.dat.article.2[res.dat.article.2$nb.dif==0,"true.gamma"] <- NA
|
|
res.dat.article.2[is.na(res.dat.article.2)] <- " "
|
|
res.dat.article.2$bias <- -1*res.dat.article.2$bias
|
|
res.dat.article.nodif.2 <- res.dat.article.2[res.dat.article.2$nb.dif==0,]
|
|
|
|
# STRATEGY 2 - ROSALI
|
|
|
|
res.dat.article.rosali <- res.dat.dif.rosali[,c("N","J","eff.size","nb.dif","dif.size",
|
|
"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
|
|
"theoretical.power")]
|
|
colnames(res.dat.article.rosali)[3] <- "true.beta"
|
|
colnames(res.dat.article.rosali)[5] <- "true.gamma"
|
|
colnames(res.dat.article.rosali)[6] <- "betahat"
|
|
colnames(res.dat.article.rosali)[8] <- "coverage"
|
|
colnames(res.dat.article.rosali)[9] <- "power"
|
|
res.dat.article.rosali[res.dat.article.rosali$true.beta==0,"typeIerror"] <- res.dat.article.rosali[res.dat.article.rosali$true.beta==0,"power"]
|
|
res.dat.article.rosali[res.dat.article.rosali$true.beta==0,"power"] <- NA
|
|
res.dat.article.rosali <- res.dat.article.rosali[,c(1:7,11,9:10,8)]
|
|
res.dat.article.rosali[res.dat.article.rosali$nb.dif==0,"true.gamma"] <- NA
|
|
res.dat.article.rosali[is.na(res.dat.article.rosali)] <- " "
|
|
res.dat.article.rosali$bias <- -1*res.dat.article.rosali$bias
|
|
res.dat.article.rosali <- reshape(res.dat.article.rosali,
|
|
direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N" )
|
|
res.dat.article.rosali.dif <- res.dat.article.rosali[res.dat.article.rosali$nb.dif>0,]
|
|
write.csv(res.dat.article.rosali.dif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_ROSALI_DIF.csv")
|
|
res.dat.article.rosali.nodif <- res.dat.article.rosali[res.dat.article.rosali$nb.dif==0,]
|
|
write.csv(res.dat.article.rosali.nodif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_ROSALI_noDIF.csv")
|
|
|
|
|
|
res.dat.article.rosali.2 <- res.dat.dif.rosali[,c("N","J","eff.size","nb.dif","dif.size",
|
|
"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
|
|
"theoretical.power")]
|
|
colnames(res.dat.article.rosali.2)[3] <- "true.beta"
|
|
colnames(res.dat.article.rosali.2)[5] <- "true.gamma"
|
|
colnames(res.dat.article.rosali.2)[6] <- "betahat"
|
|
colnames(res.dat.article.rosali.2)[8] <- "coverage"
|
|
colnames(res.dat.article.rosali.2)[9] <- "power"
|
|
res.dat.article.rosali.2[res.dat.article.rosali.2$true.beta==0,"typeIerror"] <- res.dat.article.rosali.2[res.dat.article.rosali.2$true.beta==0,"power"]
|
|
res.dat.article.rosali.2[res.dat.article.rosali.2$true.beta==0,"power"] <- NA
|
|
res.dat.article.rosali.2 <- res.dat.article.rosali.2[,c(1:7,11,9:10,8)]
|
|
res.dat.article.rosali.2[res.dat.article.rosali.2$nb.dif==0,"true.gamma"] <- NA
|
|
res.dat.article.rosali.2[is.na(res.dat.article.rosali.2)] <- " "
|
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res.dat.article.rosali.2$bias <- -1*res.dat.article.rosali.2$bias
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res.dat.article.rosali.2.nodif <- res.dat.article.rosali.2[res.dat.article.rosali.2$nb.dif==0,]
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# STRATEGY 3 - RESIDIF
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res.dat.article.residif <- res.dat.dif.resali[,c("N","J","eff.size","nb.dif","dif.size",
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"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
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"theoretical.power")]
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colnames(res.dat.article.residif)[3] <- "true.beta"
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colnames(res.dat.article.residif)[5] <- "true.gamma"
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colnames(res.dat.article.residif)[6] <- "betahat"
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colnames(res.dat.article.residif)[8] <- "coverage"
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colnames(res.dat.article.residif)[9] <- "power"
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res.dat.article.residif[res.dat.article.residif$true.beta==0,"typeIerror"] <- res.dat.article.residif[res.dat.article.residif$true.beta==0,"power"]
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res.dat.article.residif[res.dat.article.residif$true.beta==0,"power"] <- NA
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res.dat.article.residif <- res.dat.article.residif[,c(1:7,11,9:10,8)]
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res.dat.article.residif[res.dat.article.residif$nb.dif==0,"true.gamma"] <- NA
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res.dat.article.residif[is.na(res.dat.article.residif)] <- " "
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res.dat.article.residif$bias <- -1*res.dat.article.residif$bias
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res.dat.article.residif <- reshape(res.dat.article.residif,
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direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N" )
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res.dat.article.residif.dif <- res.dat.article.residif[res.dat.article.residif$nb.dif>0,]
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write.csv(res.dat.article.residif.dif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_RESIDIF_DIF.csv")
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res.dat.article.residif.nodif <- res.dat.article.residif[res.dat.article.residif$nb.dif==0,]
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write.csv(res.dat.article.residif.nodif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_RESIDIF_noDIF.csv")
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res.dat.article.residif.2 <- res.dat.dif.resali[,c("N","J","eff.size","nb.dif","dif.size",
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"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
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"theoretical.power")]
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colnames(res.dat.article.residif.2)[3] <- "true.beta"
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colnames(res.dat.article.residif.2)[5] <- "true.gamma"
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colnames(res.dat.article.residif.2)[6] <- "betahat"
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colnames(res.dat.article.residif.2)[8] <- "coverage"
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colnames(res.dat.article.residif.2)[9] <- "power"
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res.dat.article.residif.2[res.dat.article.residif.2$true.beta==0,"typeIerror"] <- res.dat.article.residif.2[res.dat.article.residif.2$true.beta==0,"power"]
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res.dat.article.residif.2[res.dat.article.residif.2$true.beta==0,"power"] <- NA
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res.dat.article.residif.2 <- res.dat.article.residif.2[,c(1:7,11,9:10,8)]
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res.dat.article.residif.2[res.dat.article.residif.2$nb.dif==0,"true.gamma"] <- NA
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res.dat.article.residif.2[is.na(res.dat.article.residif.2)] <- " "
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res.dat.article.residif.2$bias <- -1*res.dat.article.residif.2$bias
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res.dat.article.residif.2.nodif <- res.dat.article.residif.2[res.dat.article.residif.2$nb.dif==0,]
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# STRATEGY 4 - PERFECT-DIF
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res.dat.article.dif <- res.dat.dif[,c("N","J","eff.size","nb.dif","dif.size",
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"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
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"theoretical.power")]
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colnames(res.dat.article.dif)[3] <- "true.beta"
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colnames(res.dat.article.dif)[5] <- "true.gamma"
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colnames(res.dat.article.dif)[6] <- "betahat"
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colnames(res.dat.article.dif)[8] <- "coverage"
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colnames(res.dat.article.dif)[9] <- "power"
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res.dat.article.dif[res.dat.article.dif$true.beta==0,"typeIerror"] <- res.dat.article.dif[res.dat.article.dif$true.beta==0,"power"]
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res.dat.article.dif[res.dat.article.dif$true.beta==0,"power"] <- NA
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res.dat.article.dif <- res.dat.article.dif[,c(1:7,11,9:10,8)]
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res.dat.article.dif[res.dat.article.dif$nb.dif==0,"true.gamma"] <- NA
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res.dat.article.dif[is.na(res.dat.article.dif)] <- " "
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res.dat.article.dif$bias <- -1*res.dat.article.dif$bias
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write.csv(res.dat.article.dif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_perfect.csv")
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res.dat.article.dif <- reshape(res.dat.article.dif,
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direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N" )
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write.csv(res.dat.article.dif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_perfect.csv")
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res.dat.article.dif.2 <- res.dat.dif[,c("N","J","eff.size","nb.dif","dif.size",
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"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
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"theoretical.power")]
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colnames(res.dat.article.dif.2)[3] <- "true.beta"
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colnames(res.dat.article.dif.2)[5] <- "true.gamma"
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colnames(res.dat.article.dif.2)[6] <- "betahat"
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colnames(res.dat.article.dif.2)[8] <- "coverage"
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colnames(res.dat.article.dif.2)[9] <- "power"
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res.dat.article.dif.2[res.dat.article.dif.2$true.beta==0,"typeIerror"] <- res.dat.article.dif.2[res.dat.article.dif.2$true.beta==0,"power"]
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res.dat.article.dif.2[res.dat.article.dif.2$true.beta==0,"power"] <- NA
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res.dat.article.dif.2 <- res.dat.article.dif.2[,c(1:7,11,9:10,8)]
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res.dat.article.dif.2[res.dat.article.dif.2$nb.dif==0,"true.gamma"] <- NA
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res.dat.article.dif.2[is.na(res.dat.article.dif.2)] <- " "
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res.dat.article.dif.2$bias <- -1*res.dat.article.dif.2$bias
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