diff --git a/RProject/.RData b/RProject/.RData
index 2bf4797..fca6731 100644
Binary files a/RProject/.RData and b/RProject/.RData differ
diff --git a/RProject/.Rhistory b/RProject/.Rhistory
index 5f66ad1..d6992b7 100644
--- a/RProject/.Rhistory
+++ b/RProject/.Rhistory
@@ -1,201 +1,3 @@
-stop("Models RSM and GRSM cannot be used for unequal numbers of response categories!")
-}
-design_list <- design_GPCMlasso(formula = formula, data = data,
-Y = Y, RSM = RSM, GPCM = GPCM, DSF = DSF, all.dummies = control$all.dummies,
-main.effects = main.effects)
-if (design_list$m == 0) {
-control$lambda <- 0
-control$adaptive <- FALSE
-cv <- FALSE
-}
-if (length(control$lambda) == 1) {
-cv <- FALSE
-}
-loglik_fun <- loglikPCMlasso
-score_fun <- scorePCMlasso
-log_score_fun <- loglikscorePCMlasso2
-if (all(k == 2)) {
-loglik_fun <- loglikDIFlasso
-score_fun <- scoreDIFlasso
-log_score_fun <- loglikscoreDIFlasso2
-}
-fit <- fit_GPCMlasso(model = model, loglik_fun = loglik_fun, acoefs2 = acoefs2,
-score_fun = score_fun, log_score_fun, design_list = design_list,
-control = control, start = NULL, scale_fac = 1, main.effects = main.effects)
-if (is.null(control$lambda)) {
-control$lambda <- fit$lambda
-}
-coefficients <- fit$coefficients
-coef.rescal <- fit$coef.rescal
-logLik <- fit$logLik
-df <- fit$df
-BIC <- -2 * logLik + log(design_list$n) * df
-AIC <- -2 * logLik + 2 * df
-cAIC <- -2 * logLik + 2 * df + 2 * df * (df - 1)/(design_list$n -
-df - 1)
-if (cv) {
-cv_error <- fit_cv_GPCMlasso(model, design_list, control,
-score_fun, loglik_fun, log_score_fun, Y)
-}
-else {
-cv_error <- NULL
-}
-ret.list <- list(coefficients = coefficients, logLik = logLik,
-cv_error = cv_error, call = match.call(), model = model,
-data = data, control = control, DSF = DSF, formula = formula,
-item.names = item.names, Y = Y, design_list = design_list,
-AIC = AIC, BIC = BIC, cAIC = cAIC, df = df, coef.rescal = coef.rescal,
-main.effects = main.effects)
-class(ret.list) <- "GPCMlasso"
-return(ret.list)
-}
-GPCMlasso2 <- function (formula, data, DSF = FALSE, model = c("PCM", "RSM",
-"GPCM", "GRSM", "RM", "2PL"), control = ctrl_GPCMlasso(),
-cv = FALSE, main.effects = TRUE,acoefs2=NULL)
-{
-if (!is.data.frame(data))
-stop("data has to be a data.frame!")
-Y <- model.response(model.frame(formula, data = data))
-for (i in 1:ncol(Y)) {
-Y[, i] <- as.factor(Y[, i])
-}
-item.names <- colnames(Y)
-model <- match.arg(model)
-RSM <- GPCM <- FALSE
-if (model %in% c("GRSM", "RSM")) {
-RSM <- TRUE
-}
-if (model %in% c("GRSM", "GPCM", "2PL")) {
-GPCM <- TRUE
-}
-k <- apply(Y, 2, function(x) {
-length(levels(as.factor(x)))
-})
-if (all(k == 2) | model %in% c("RM", "2PL")) {
-DSF <- FALSE
-control$cv.crit <- "deviance"
-}
-if (length(unique(k)) > 1 & RSM) {
-stop("Models RSM and GRSM cannot be used for unequal numbers of response categories!")
-}
-design_list <- design_GPCMlasso(formula = formula, data = data,
-Y = Y, RSM = RSM, GPCM = GPCM, DSF = DSF, all.dummies = control$all.dummies,
-main.effects = main.effects)
-if (design_list$m == 0) {
-control$lambda <- 0
-control$adaptive <- FALSE
-cv <- FALSE
-}
-if (length(control$lambda) == 1) {
-cv <- FALSE
-}
-loglik_fun <- loglikPCMlasso
-score_fun <- scorePCMlasso
-log_score_fun <- loglikscorePCMlasso2
-if (all(k == 2)) {
-loglik_fun <- loglikDIFlasso
-score_fun <- scoreDIFlasso
-log_score_fun <- loglikscoreDIFlasso2
-}
-fit <- fit_GPCMlasso(model = model, loglik_fun = loglik_fun, acoefs2 = acoefs2,
-score_fun = score_fun, log_score_fun, design_list = design_list,
-control = control, start = NULL, scale_fac = 1, main.effects = main.effects)
-if (is.null(control$lambda)) {
-control$lambda <- fit$lambda
-}
-coefficients <- fit$coefficients
-coef.rescal <- fit$coef.rescal
-logLik <- fit$logLik
-df <- fit$df
-BIC <- -2 * logLik + log(design_list$n) * df
-AIC <- -2 * logLik + 2 * df
-cAIC <- -2 * logLik + 2 * df + 2 * df * (df - 1)/(design_list$n -
-df - 1)
-if (cv) {
-cv_error <- fit_cv_GPCMlasso(model, design_list, control,
-score_fun, loglik_fun, log_score_fun, Y)
-}
-else {
-cv_error <- NULL
-}
-ret.list <- list(coefficients = coefficients, logLik = logLik,
-cv_error = cv_error, call = match.call(), model = model,
-data = data, control = control, DSF = DSF, formula = formula,
-item.names = item.names, Y = Y, design_list = design_list,
-AIC = AIC, BIC = BIC, cAIC = cAIC, df = df, coef.rescal = coef.rescal,
-main.effects = main.effects)
-class(ret.list) <- "GPCMlasso"
-return(ret.list)
-}
-GPCMlasso2(formula = cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control=ctrl_GPCMlasso(lambda=0.0000000000001),acoefs2 = u)
-u
-## create responses for acat from ordinal values
-createResponse <- function(Y){
-Y <- as.factor(Y)
-model.matrix(~0+Y)[,-length(levels(Y))]
-}
-design_GPCMlasso <- function(formula = formula, Y=Y, data = data, RSM = RSM,
-GPCM = GPCM, DSF = DSF, all.dummies = TRUE, main.effects = main.effects){
-## extract covariates
-if(all.dummies){
-term.labels <- attr(terms(formula), "term.labels")
-X <- matrix(rep(1,nrow(data)))
-for(ij in 1:length(term.labels)){
-x.now <- data[,term.labels[ij], drop = FALSE]
-if(is.factor(x.now[,1])){
-if(nlevels(x.now[,1])==2){
-X <- cbind(X,model.matrix(~.,data=x.now)[,-1,drop=FALSE])
-}else{
-X <- cbind(X,model.matrix(~0+.,data=x.now))
-}
-}else{
-X <- cbind(X,model.matrix(~.,data=x.now)[,-1,drop=FALSE])
-}
-}
-X <- X[,-1,drop = FALSE]
-}else{
-X <- model.matrix(formula, data = data)
-if(ncol(X)>=1){
-if(colnames(X)[1]=="(Intercept)"){
-X <- X[,-1,drop = FALSE]
-}
-}
-}
-x.names <- colnames(X)
-## factorize response vector
-## initialize basic parameters
-k <- apply(Y, 2, function(x){length(levels(as.factor(x)))})
-q <- k-1
-n <- nrow(Y)
-I <- ncol(Y)
-m <- ncol(X)
-n_sigma <- 1
-if(GPCM){
-n_sigma <- I
-}
-## get final response vector
-if(all(q==1)){
-response <- as.numeric(as.factor(c(t(Y))))-1
-}else{
-response <- lapply(as.data.frame(Y),createResponse)
-response <- c(t(do.call("cbind",response)))
-}
-## total number of parameters to be optimized
-px <- sum(q)+n_sigma
-if(RSM){
-px <- q[1]+I+n_sigma-1
-}
-## scale X and save standard deviations for re-scaling
-# X <- scale(X, center = FALSE)
-X <- scale(X, center = FALSE, scale = apply(X, 2, sd, na.rm = TRUE))
-sd.vec <- attributes(X)$scale
-sd.vec <- create.sd.vec(sd.vec, DSF, px, n_sigma, I, q, main.effects)
-## create design matrix for basic item parameters
-if(!RSM){
-design <- -diag(px-n_sigma)
-}else{
-design <- -cbind(matrix(rep(diag(I),each=q[1]),ncol=I),
-matrix(rep(diag(q[1]),I),ncol=q[1],byrow = TRUE))[,-(I+1)]
 }
 ## create design matrix for covariate part
 if(m>=1){
@@ -510,3 +312,201 @@ GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT:item1tt+TT:item2TT+TT:item3t
 GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT:item1tt+TT:item2tt+TT:item3tt+TT:item4tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
 GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT*item1tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
 GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT*item1tt+TT*item2tt+TT*item3tt+TT*item4tt,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+library(mirt)
+model.pcm <- "hrqol = 1-4"
+mirt(data = aaaa[,paste0("item",1:4)])
+mirt(data = aaaa[,paste0("item",1:4)],model=model.pcm,itemtype = "Rasch",SE=T)
+coef(mirt(data = aaaa[,paste0("item",1:4)],model=model.pcm,itemtype = "Rasch",SE=T))
+coef(mirt(data = aaaa[,paste0("item",1:4)],model=model.pcm,itemtype = "PCM",SE=T))
+coef(mirt(data = aaaa[,paste0("item",1:4)],model=model.pcm,itemtype = "GPCM",SE=T))
+coef(mirt(data = aaaa[,paste0("item",1:4)],model=model.pcm,itemtype = "Rasch",SE=T))
+coef.pcm <- coef(mirt(data = aaaa[,paste0("item",1:4)],model=model.pcm,itemtype = "Rasch",SE=T),IRTpars=T,simplify=T)
+coef.pcm
+coef.pcm <- coef(multipleGroup(data = aaaa[,paste0("item",1:4)],group="TT",model=model.pcm,itemtype = "Rasch",SE=T),IRTpars=T,simplify=T)
+multipleGroup(data = aaaa[,paste0("item",1:4)],group="TT",model=model.pcm,itemtype = "Rasch",SE=T)
+coef.pcm <- coef(multipleGroup(data = aaaa[,paste0("item",1:4)],group=aaaa$TT,model=model.pcm,itemtype = "Rasch",SE=T),IRTpars=T,simplify=T)
+coef.pcm <- coef(multipleGroup(data = aaaa[,paste0("item",1:4)],group=as.character(aaaa$TT),model=model.pcm,itemtype = "Rasch",SE=T),IRTpars=T,simplify=T)
+coef.pcm
+library(TAM)
+tam.mml(resp=aaaa[,c("item1","item2","item3","item4")],group=aaaa$TT)
+coef.pcm
+coef.pcm <- coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa$TT,formula=hrqol~TT,model=model.pcm,itemtype = "Rasch",SE=T),IRTpars=T,simplify=T)
+coef.pcm <- coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=hrqol~TT,model=model.pcm,itemtype = "Rasch",SE=T),IRTpars=T,simplify=T)
+coef.pcm <- coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=c(hrqol=as.formula("~TT")),model=model.pcm,itemtype = "Rasch",SE=T),IRTpars=T,simplify=T)
+coef.pcm <- coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=c(hrqol=as.formula("~TT")),model=model.pcm,itemtype = "Rasch",SE=T))
+mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=c(hrqol=as.formula("~TT")),model=model.pcm,itemtype = "Rasch",SE=T)
+mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch",SE=T)
+mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch")
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch"))
+tam.mml(resp=aaaa[,c("item1","item2","item3","item4")],group=aaaa$TT)
+mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch")
+aaa <- read.csv(paste0('/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N',100,'/scenario_',"6A_100",'.csv'))
+aaaa <- aaa[aaa$replication==1,]
+tam.mml(resp=aaaa[,c("item1","item2","item3","item4")],group=aaaa$TT)
+mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "GPCM")
+mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch")
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch"))
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch"),simplify=T)
+coef(tam.mml(resp=aaaa[,c("item1","item2","item3","item4")],group=aaaa$TT))
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch"),simplify=T)
+model.pcm <- "hrqol = 1*TT+2-4"
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch"),simplify=T)
+model.pcm <- "hrqol = 1-4"
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT,model=model.pcm,itemtype = "Rasch"),simplify=T)
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT+TT:item1,model=model.pcm,itemtype = "Rasch"),simplify=T)
+aaaa$dif1
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT+TT:item4,model=model.pcm,itemtype = "Rasch"),simplify=T)
+tam.mml(resp=aaaa[,c("item1","item2","item3","item4")],group=aaaa$TT)
+aaaa[aaaa$TT==1,]$item4TT <- aaaa[aaaa$TT==1,]$item4
+aaaa
+aaaa[aaaa$TT==1,]$item4TT <- aaaa[aaaa$TT==1,]$item4
+aaaa[aaaa$TT==1,]$item4
+aaaa
+aaaa[aaaa$TT==1,]$item4TT <- 0
+aaaa[aaaa$TT==1,]$item4TT
+aaaa[aaaa$TT==1,]
+aaaa[aaaa$TT==1,"item4tt"] <- aaaa[aaaa$TT==1,"item4"]
+aaaa
+aaaa[aaaa$TT==0,"item4nott"] <- aaaa[aaaa$TT==0,"item4"]
+tam.mml(resp=aaaa[,c("item1","item2","item3","item4tt","item4nott")],group=aaaa$TT)
+Summary(tam.mml(resp=aaaa[,c("item1","item2","item3","item4tt","item4nott")],group=aaaa$TT))
+summary(tam.mml(resp=aaaa[,c("item1","item2","item3","item4tt","item4nott")],group=aaaa$TT))
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT+TT:item4,model=model.pcm,itemtype = "Rasch"),simplify=T,IRTpars=T)
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa,formula=~TT+TT:item4,model=model.pcm,itemtype = "Rasch"),simplify=T,IRTpars=T)
+aaaa
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa[,1:9],formula=~TT+TT:item4,model=model.pcm,itemtype = "Rasch"),simplify=T,IRTpars=T)
+summary(tam.mml(resp=aaaa[,c("item1","item2","item3","item4tt","item4nott")],group=aaaa$TT))
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa[,1:9],formula=~TT+TT:item4,model=model.pcm,itemtype = "Rasch"),simplify=T,IRTpars=T)
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa[,1:9],formula=~TT+TT*item4,model=model.pcm,itemtype = "Rasch"),simplify=T,IRTpars=T)
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa[,1:9],formula=~TT+TT:item4,model=model.pcm,itemtype = "Rasch"),simplify=T,IRTpars=T)
+coef(mirt(data = aaaa[,paste0("item",1:4)],covdata=aaaa[,1:9],formula=~TT,model=model.pcm,itemtype = "Rasch"),simplify=T,IRTpars=T)
+model.pcm <- "hrqol = 1-4"
+multipleGroup(data = aaaa[,paste0("item",1:4)],group=as.character(aaaa$TT),model=model.pcm,itemtype = "Rasch")
+zzz <- multipleGroup(data = aaaa[,paste0("item",1:4)],group=as.character(aaaa$TT),model=model.pcm,itemtype = "Rasch")
+DIF(zzz,items2test = 4,groups2test = "TT")
+DIF(zzz,items2test = 4,groups2test = "TT",which.par = c("a1","d"))
+DIF(zzz,items2test = 4,groups2test = "TT",which.par = c("hrqol"))
+DIF(zzz,items2test = 4,groups2test = "TT",which.par = c("item1"))
+zzz
+coef(zzz)
+DIF(zzz,items2test = 4,groups2test = "TT",which.par = c("a1"))
+DIF(zzz,items2test = 4,which.par = c("a1"))
+DIF(zzz,items2test = 4,which.par = c("a1"),return_models = T)
+DIF(zzz,items2test = 4,which.par = c("a1"),return_models = T)
+DIF(zzz,items2test = 4,which.par = c("a1"),return_models = F)
+zzzz<- DIF(zzz,items2test = 4,which.par = c("a1"))
+zzzz<- DIF(zzz,items2test = 4,which.par = c("a1"),return_seq_model = T)
+zzzz<- DIF(zzz,items2test = 4,which.par = c("g"),return_seq_model = T)
+coef(zzz)
+zzzz<- DIF(zzz,items2test = 4,which.par = c("d1","d2","d3"),return_model = T)
+zzzz<- DIF(zzz,items2test = 4,which.par = c("d1","d2","d3"))
+zzzz
+install.packages('/home/corentin/Documents/These/Packages/GPCMlasso_0.1-7.tar.gz')
+library(GPCMlasso)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000000000),DSF = F,cv=F)
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+library(TAM)
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+coef(tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT))
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0.1),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+?GPCMlasso
+?GPCMlasso
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F,main.effects = F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000),DSF = F,cv=F,main.effects = F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4,item4tt)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+aaaa[aaaa$TT==1,"item4tt"] <- aaaa[aaaa$TT==1,"item4"]
+GPCMlasso(formula=cbind(item1,item2,item3,item4,item4tt)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4,item4tt)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4tt)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10),DSF = F,cv=F)
+0.265*log(10)
+0.265*log(100)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000),DSF = F,cv=F)
+0.265/1/log(100)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000),DSF = F,cv=F)$coef.rescal
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 100000000000),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)$coefficients
+install.packages("/home/corentin/Documents/These/Packages/GPCMlasso_0.1-7.tar.gz")
+library(GPCMlasso)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+library(TAM)
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0),DSF = F,cv=F)
+tam.mml(aaaa[,c("item1","item2","item3",'item4')])
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0,lambda2=0),DSF = F,cv=F)
+install.packages("/home/corentin/Documents/These/Packages/GPCMlasso_0.1-7.tar.gz")
+library(GPCMlasso)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0,lambda2=0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 1000,lambda2=0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0,lambda2=1000),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0,lambda2=0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0,lambda2=100),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 100,lambda2=0),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 100,lambda2=0,adaptative=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 100,lambda2=0,adaptive=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0,adaptive=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 0,adaptive=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F)$coefficients
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F)$coef.rescal
+library(TAM)
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=1e-8,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=1e-4,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=1e-18,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=1e-2,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=1e-3,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=1e-2.5,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0.0005,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0.001,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0.01,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0.005,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0.002,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=-1,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=-0.1,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=-0.0001,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=-10,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=-10000,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=-100000,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=10000000000000000000000000000000000000000,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=-10000000000000000000000000000000000000000,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,lambda2=0,adaptive=F),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,ada.lambda=0,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,ada.lambda=1000,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,ada.lambda=-1000,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,ada.lambda=-10,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,ada.lambda=0,adaptive=T),DSF = F,cv=F)$coef.rescal
+0.265/0.09
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,ada.lambda=0,adaptive=T),DSF = F,cv=F)$coef.rescal
+1.1479/0.4403
+0.265/0.09
+0.265/0.036
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
+1.1479/0.0001
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,ada.power=2,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=0,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=0.000001,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=1,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="PCM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=10000,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="RM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=10000,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GRM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=10000,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="2PL",control = ctrl_GPCMlasso(lambda = 10000,cvalue=10000,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GPCM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=10000,adaptive=T),DSF = F,cv=F)$coef.rescal
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GPCM",control = ctrl_GPCMlasso(lambda = 10000,cvalue=10000,adaptive=T),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GPCM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GPCM",control = ctrl_GPCMlasso(lambda = 10000000,adaptive=F),DSF = F,cv=F)
+GPCMlasso(formula=cbind(item1,item2,item3,item4)~TT,data=aaaa,model="GRSM",control = ctrl_GPCMlasso(lambda = 10000,adaptive=F),DSF = F,cv=F)
+tam.mml(aaaa[,c("item1","item2","item3",'item4')],group=aaaa$TT)
diff --git a/RProject/resali.R b/RProject/Scripts/resali.R
similarity index 100%
rename from RProject/resali.R
rename to RProject/Scripts/resali.R
diff --git a/Scripts/Analysis/DIF-RESIDUS/pcm_dif_residus.do b/Scripts/Analysis/DIF-RESIDUS/pcm_dif_residus.do
index a936341..53e0e26 100644
--- a/Scripts/Analysis/DIF-RESIDUS/pcm_dif_residus.do
+++ b/Scripts/Analysis/DIF-RESIDUS/pcm_dif_residus.do
@@ -1,1513 +1,364 @@
-  *=================================================================================================================================================
-  * Date : 2024-01-23
-  * Stata version : Stata 18 SE
-  *
-  * This program analyses simulated data accounting for DIF through a partial credit model
-  *
-  * ado-files needed : - pcm (version 5.5 October 25, 2023, available on gitea)
-  *
-  *
-  *================================================================================================================================================
-
-  * Load pcm.ado
-  adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
-
-  *==========================
-  * Scenarios with : J=4
-  *==========================
-
-  ****** Scenarios with DIF on 1 item
-
-  ** Scenario 5: J = 4 items / M = 2 modalities / DIF size 0.3
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_5`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 4
-  local nbdif = 1
-  local taillemat = `nbitems'+`nbdif'+3
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "dif1" "beta" "se_beta" "dif_item_1"
-  di "Scenario 5`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitems1') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitems1') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitems1'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`nbitems'+2] // beta
-    mat outmat[`k',`nbitems'+3] = W[2,3*`nbitems'+2] // se beta
-    mat outmat[`k',`nbitems'+4] = `difitems1' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/5`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-** Scenario 6: J = 4 items / M = 4 modalities / DIF size 0.3
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_6`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 4
-local nbdif = 1
-local taillemat = 3*`nbitems'+`nbdif'+3+2
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "dif1_1" "dif1_2" "dif1_3" "beta" "se_beta" "dif_item_1"
-di "Scenario 6`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitems1') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitems1') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitems1') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitems1') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitems1'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitems1'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitems1'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*`nbitems'+4] // beta
-    mat outmat[`k',3*`nbitems'+5] = W[2,7*`nbitems'+4] // se beta
-    mat outmat[`k',3*`nbitems'+6] = `difitems1' // numéro item de dif
-    restore
-}
-putexcel set "`path_res'/6`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-** Scenario 7: J = 4 items / M = 2 modalities / DIF size 0.5
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_7`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 4
-  local nbdif = 1
-  local taillemat = `nbitems'+`nbdif'+3
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "dif1" "beta" "se_beta" "dif_item_1"
-  di "Scenario 7`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitems1') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitems1') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitems1'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`nbitems'+2] // beta
-    mat outmat[`k',`nbitems'+3] = W[2,3*`nbitems'+2] // se beta
-    mat outmat[`k',`nbitems'+4] = `difitems1' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/7`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-** Scenario 8: J = 4 items / M = 4 modalities / DIF size 0.5
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_8`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 4
-local nbdif = 1
-local taillemat = 3*`nbitems'+`nbdif'+3+2
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "dif1_1" "dif1_2" "dif1_3" "beta" "se_beta" "dif_item_1"
-di "Scenario 8`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitems1') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitems1') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitems1') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitems1') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitems1'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitems1'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitems1'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*`nbitems'+4] // beta
-    mat outmat[`k',3*`nbitems'+5] = W[2,7*`nbitems'+4] // se beta
-    mat outmat[`k',3*`nbitems'+6] = `difitems1' // numéro item de dif
-    restore
-}
-putexcel set "`path_res'/8`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-****** Scenarios with DIF on 2 items
-
-* Load pcm.ado
-adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
-
-** Scenario 9: J = 4 items / M = 2 modalities / DIF size 0.3 x2
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_9`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 4
-  local nbdif = 2
-  local taillemat = `nbitems'+`nbdif'+4
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "dif1" "dif2" "beta" "se_beta" "dif_item_1" "dif_item_2"
-  di "Scenario 9`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local difitems2=dif2
-    if (`difitems1'<`difitems2') {
-      local difitemsmin `difitems1'
-      local difitemsmax `difitems2'
-    }
-    else {
-      local difitemsmin `difitems2'
-      local difitemsmax `difitems1'
-    }
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitemsmin') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else if (`j'<`difitemsmax') {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,2+3*`j'] // items après le deuxieme dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitemsmin'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`difitemsmax'] // coef de dif
-    mat outmat[`k',`nbitems'+3] = W[1,3*`nbitems'+3] // beta
-    mat outmat[`k',`nbitems'+4] = W[2,3*`nbitems'+3] // se beta
-    mat outmat[`k',`nbitems'+5] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',`nbitems'+6] = `difitemsmax' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/9`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 10: J = 4 items / M = 4 modalities / DIF size 0.3 x2
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_10`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 4
-local nbdif = 2
-local taillemat = 3*`nbitems'+6+2+`nbdif'
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "dif1_1" "dif1_2" "dif1_3" "dif2_1" "dif2_2" "dif2_3" "beta" "se_beta" "dif_item_1" "dif_item_2"
-di "Scenario 10`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  local difitems2=dif2
-  if (`difitems1'<`difitems2') {
-    local difitemsmin `difitems1'
-    local difitemsmax `difitems2'
-  }
-  else {
-    local difitemsmin `difitems2'
-    local difitemsmax `difitems1'
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmax') {
-      local constrn3 = "constraint 3 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt4 = "constraint 4 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2 3 4)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `constrnt3'
-  qui `constrnt4'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else if (`j'<`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  else if (`j'==`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+7] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+10] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-    }
-  else {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+9] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+11] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-  }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitemsmin'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitemsmin'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitemsmin'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*(`difitemsmax'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+5] = W[1,7*(`difitemsmax'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+6] = W[1,7*(`difitemsmax'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+7] = W[1,7*`nbitems'+7] // beta
-    mat outmat[`k',3*`nbitems'+8] = W[2,7*`nbitems'+7] // se beta
-    mat outmat[`k',3*`nbitems'+9] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+10] = `difitemsmax' // numéro item de dif
-    restore
-}
-putexcel set "`path_res'/10`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 11: J = 4 items / M = 2 modalities / DIF size 0.5 x2
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_11`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 4
-  local nbdif = 2
-  local taillemat = `nbitems'+`nbdif'+4
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "dif1" "dif2" "beta" "se_beta" "dif_item_1" "dif_item_2"
-  di "Scenario 11`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local difitems2=dif2
-    if (`difitems1'<`difitems2') {
-      local difitemsmin `difitems1'
-      local difitemsmax `difitems2'
-    }
-    else {
-      local difitemsmin `difitems2'
-      local difitemsmax `difitems1'
-    }
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitemsmin') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else if (`j'<`difitemsmax') {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,2+3*`j'] // items après le deuxieme dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitemsmin'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`difitemsmax'] // coef de dif
-    mat outmat[`k',`nbitems'+3] = W[1,3*`nbitems'+3] // beta
-    mat outmat[`k',`nbitems'+4] = W[2,3*`nbitems'+3] // se beta
-    mat outmat[`k',`nbitems'+5] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',`nbitems'+6] = `difitemsmax' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/11`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 12: J = 4 items / M = 4 modalities / DIF size 0.5 x2
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_12`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 4
-local nbdif = 2
-local taillemat = 3*`nbitems'+6+2+`nbdif'
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "dif1_1" "dif1_2" "dif1_3" "dif2_1" "dif2_2" "dif2_3" "beta" "se_beta" "dif_item_1" "dif_item_2"
-di "Scenario 12`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  local difitems2=dif2
-  if (`difitems1'<`difitems2') {
-    local difitemsmin `difitems1'
-    local difitemsmax `difitems2'
-  }
-  else {
-    local difitemsmin `difitems2'
-    local difitemsmax `difitems1'
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmax') {
-      local constrn3 = "constraint 3 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt4 = "constraint 4 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2 3 4)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `constrnt3'
-  qui `constrnt4'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else if (`j'<`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  else if (`j'==`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+7] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+10] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-    }
-  else {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+9] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+11] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-  }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitemsmin'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitemsmin'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitemsmin'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*(`difitemsmax'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+5] = W[1,7*(`difitemsmax'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+6] = W[1,7*(`difitemsmax'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+7] = W[1,7*`nbitems'+7] // beta
-    mat outmat[`k',3*`nbitems'+8] = W[2,7*`nbitems'+7] // se beta
-    mat outmat[`k',3*`nbitems'+9] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+10] = `difitemsmax' // numéro item de dif
-    restore
-}
-putexcel set "`path_res'/12`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-*==========================
-* Scenarios with : J=7
-*==========================
-
-
-****** Scenarios with DIF on 2 items
-
-* Load pcm.ado
-adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
-
-** Scenario 13: J = 7 items / M = 2 modalities / DIF size 0.3 x2
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_13`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 7
-  local nbdif = 2
-  local taillemat = `nbitems'+`nbdif'+4
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "item5" "item6" "item7" "dif1" "dif2" "beta" "se_beta" "dif_item_1" "dif_item_2"
-  di "Scenario 13`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local difitems2=dif2
-    if (`difitems1'<`difitems2') {
-      local difitemsmin `difitems1'
-      local difitemsmax `difitems2'
-    }
-    else {
-      local difitemsmin `difitems2'
-      local difitemsmax `difitems1'
-    }
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitemsmin') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else if (`j'<`difitemsmax') {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,2+3*`j'] // items après le deuxieme dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitemsmin'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`difitemsmax'] // coef de dif
-    mat outmat[`k',`nbitems'+3] = W[1,3*`nbitems'+3] // beta
-    mat outmat[`k',`nbitems'+4] = W[2,3*`nbitems'+3] // se beta
-    mat outmat[`k',`nbitems'+5] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',`nbitems'+6] = `difitemsmax' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/13`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 14: J = 7 items / M = 4 modalities / DIF size 0.3 x2
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_14`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 7
-local nbdif = 2
-local taillemat = 3*`nbitems'+6+2+`nbdif'
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "item5_1" "item5_2" "item5_3" "item6_1" "item6_2" "item6_3" "item7_1" "item7_2" "item7_3" "dif1_1" "dif1_2" "dif1_3" "dif2_1" "dif2_2" "dif2_3" "beta" "se_beta" "dif_item_1" "dif_item_2"
-di "Scenario 14`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  local difitems2=dif2
-  if (`difitems1'<`difitems2') {
-    local difitemsmin `difitems1'
-    local difitemsmax `difitems2'
-  }
-  else {
-    local difitemsmin `difitems2'
-    local difitemsmax `difitems1'
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmax') {
-      local constrn3 = "constraint 3 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt4 = "constraint 4 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2 3 4)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `constrnt3'
-  qui `constrnt4'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else if (`j'<`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  else if (`j'==`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+7] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+10] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-    }
-  else {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+9] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+11] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-  }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitemsmin'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitemsmin'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitemsmin'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*(`difitemsmax'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+5] = W[1,7*(`difitemsmax'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+6] = W[1,7*(`difitemsmax'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+7] = W[1,7*`nbitems'+7] // beta
-    mat outmat[`k',3*`nbitems'+8] = W[2,7*`nbitems'+7] // se beta
-    mat outmat[`k',3*`nbitems'+9] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+10] = `difitemsmax' // numéro item de dif
-    restore
-}
-putexcel set "`path_res'/14`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 15: J = 7 items / M = 2 modalities / DIF size 0.5 x2
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_15`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 7
-  local nbdif = 2
-  local taillemat = `nbitems'+`nbdif'+4
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "item5" "item6" "item7" "dif1" "dif2" "beta" "se_beta" "dif_item_1" "dif_item_2"
-  di "Scenario 15`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local difitems2=dif2
-    if (`difitems1'<`difitems2') {
-      local difitemsmin `difitems1'
-      local difitemsmax `difitems2'
-    }
-    else {
-      local difitemsmin `difitems2'
-      local difitemsmax `difitems1'
-    }
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitemsmin') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else if (`j'<`difitemsmax') {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,2+3*`j'] // items après le deuxieme dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitemsmin'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`difitemsmax'] // coef de dif
-    mat outmat[`k',`nbitems'+3] = W[1,3*`nbitems'+3] // beta
-    mat outmat[`k',`nbitems'+4] = W[2,3*`nbitems'+3] // se beta
-    mat outmat[`k',`nbitems'+5] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',`nbitems'+6] = `difitemsmax' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/15`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 16: J = 7 items / M = 4 modalities / DIF size 0.5 x2
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_16`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 7
-local nbdif = 2
-local taillemat = 3*`nbitems'+6+2+`nbdif'
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "item5_1" "item5_2" "item5_3" "item6_1" "item6_2" "item6_3" "item7_1" "item7_2" "item7_3" "dif1_1" "dif1_2" "dif1_3" "dif2_1" "dif2_2" "dif2_3" "beta" "se_beta" "dif_item_1" "dif_item_2"
-di "Scenario 16`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  local difitems2=dif2
-  if (`difitems1'<`difitems2') {
-    local difitemsmin `difitems1'
-    local difitemsmax `difitems2'
-  }
-  else {
-    local difitemsmin `difitems2'
-    local difitemsmax `difitems1'
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmax') {
-      local constrn3 = "constraint 3 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt4 = "constraint 4 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin' | `i'==`difitemsmax') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2 3 4)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `constrnt3'
-  qui `constrnt4'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else if (`j'<`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  else if (`j'==`difitemsmax') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+7] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+10] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-    }
-  else {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+9] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+11] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-  }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitemsmin'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitemsmin'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitemsmin'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*(`difitemsmax'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+5] = W[1,7*(`difitemsmax'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+6] = W[1,7*(`difitemsmax'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+7] = W[1,7*`nbitems'+7] // beta
-    mat outmat[`k',3*`nbitems'+8] = W[2,7*`nbitems'+7] // se beta
-    mat outmat[`k',3*`nbitems'+9] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+10] = `difitemsmax' // numéro item de dif
-    restore
-}
-putexcel set "`path_res'/16`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
-}
-}
-
-***** Scenarios with DIF on 3 items
-
-* Load pcm.ado
-adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
-
-** Scenario 17: J = 7 items / M = 2 modalities / DIF size 0.3 x3
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_17`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 7
-  local nbdif = 3
-  local taillemat = `nbitems'+`nbdif'+5
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "item5" "item6" "item7" "dif1" "dif2" "dif3" "beta" "se_beta" "dif_item_1" "dif_item_2" "dif_item_3"
-  di "Scenario 17`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local difitems2=dif2
-    local difitems3=dif3
-    if (`difitems1' < `difitems2') {
-      local difitemsmin= `difitems1'
-      local difitemsmax= `difitems2'
-    }
-    else {
-      local difitemsmin= `difitems2'
-      local difitemsmax= `difitems1'
-    }
-    if (`difitems3' < `difitemsmin') {
-      local difitemsmid = `difitemsmin'
-      local difitemsmin= `difitems3'
-    }
-    else if (`difitems3' > `difitemsmax') {
-      local difitemsmid = `difitemsmax'
-      local difitemsmax= `difitems3'
-    }
-    else {
-      local difitemsmid = `difitems3'
-    }
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitemsmin' | `i'==`difitemsmax' | `i'==`difitemsmid') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitemsmin') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else if (`j'<`difitemsmid') {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-      else if (`j'<`difitemsmax') {
-        mat outmat[`k',`j'] = W[1,2+3*`j'] // items après le deuxieme dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,3+3*`j'] // items après le deuxieme dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitemsmin'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`difitemsmid'] // coef de dif
-    mat outmat[`k',`nbitems'+3] = W[1,3*`difitemsmax'+1] // coef de dif
-    mat outmat[`k',`nbitems'+4] = W[1,3*`nbitems'+4] // beta
-    mat outmat[`k',`nbitems'+5] = W[2,3*`nbitems'+4] // se beta
-    mat outmat[`k',`nbitems'+6] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',`nbitems'+7] = `difitemsmid' // numéro item de dif
-    mat outmat[`k',`nbitems'+8] = `difitemsmax' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/17`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 18: J = 7 items / M = 4 modalities / DIF size 0.3 x3
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_18`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 7
-local nbdif = 3
-local taillemat = 3*`nbitems'+9+2+`nbdif'
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "item5_1" "item5_2" "item5_3" "item6_1" "item6_2" "item6_3" "item7_1" "item7_2" "item7_3" "dif1_1" "dif1_2" "dif1_3" "dif2_1" "dif2_2" "dif2_3" "dif3_1" "dif3_2" "dif3_3" "beta" "se_beta" "dif_item_1" "dif_item_2" "dif_item_3"
-di "Scenario 18`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  local difitems2=dif2
-  local difitems3=dif3
-  if (`difitems1' < `difitems2') {
-    local difitemsmin= `difitems1'
-    local difitemsmax= `difitems2'
-  }
-  else {
-    local difitemsmin= `difitems2'
-    local difitemsmax= `difitems1'
-  }
-  if (`difitems3' < `difitemsmin') {
-    local difitemsmid = `difitemsmin'
-    local difitemsmin= `difitems3'
-  }
-  else if (`difitems3' > `difitemsmax') {
-    local difitemsmid = `difitemsmax'
-    local difitemsmax= `difitems3'
-  }
-  else {
-    local difitemsmid = `difitems3'
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmax') {
-      local constrn3 = "constraint 3 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt4 = "constraint 4 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmid') {
-      local constrn5 = "constraint 5 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt6 = "constraint 6 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin' | `i'==`difitemsmax' | `i'==`difitemsmid') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2 3 4 5 6)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `constrnt3'
-  qui `constrnt4'
-  qui `constrnt6'
-  qui `constrnt6'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else if (`j'<`difitemsmid') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  else if (`j'==`difitemsmid') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+7] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+10] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-    }
-  else if (`j'<`difitemsmax') {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+9] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+11] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-  }
-  else if (`j'==`difitemsmax') {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+10] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+13] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+16] // items avant le premier dif
-  }
-  else {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+12] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+14] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+16] // items avant le premier dif
-  }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitemsmin'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitemsmin'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitemsmin'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*(`difitemsmid'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+5] = W[1,7*(`difitemsmid'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+6] = W[1,7*(`difitemsmid'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+7] = W[1,7*(`difitemsmax'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+8] = W[1,7*(`difitemsmax'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+9] = W[1,7*(`difitemsmax'-1)+14] // coef de dif
-    mat outmat[`k',3*`nbitems'+10] = W[1,7*`nbitems'+10] // beta
-    mat outmat[`k',3*`nbitems'+11] = W[2,7*`nbitems'+10] // se beta
-    mat outmat[`k',3*`nbitems'+12] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+13] = `difitemsmid' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+14] = `difitemsmax' // numéro item de dif
-    restore
-}
-putexcel set "`path_res'/18`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
-}
-}
-
-** Scenario 19: J = 7 items / M = 2 modalities / DIF size 0.5 x3
-  local N = "100 200 300"
-  foreach Nnn in `N' {
-  local Nn =  `Nnn'
-  local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-  local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-  local scenarios = "A B C D E F G"
-  foreach scen in `scenarios' {
-  clear
-  import delim "`path_data'/scenario_19`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-  rename TT tt
-
-  * Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-  local nbitems = 7
-  local nbdif = 3
-  local taillemat = `nbitems'+`nbdif'+5
-  mat outmat = J(1000,`taillemat',.)
-  mat colnames outmat = "item1" "item2" "item3" "item4" "item5" "item6" "item7" "dif1" "dif2" "dif3" "beta" "se_beta" "dif_item_1" "dif_item_2" "dif_item_3"
-  di "Scenario 19`scen' / N=`Nnn'"
-  forvalues k=1/1000 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
-    preserve
-    qui keep if replication==`k'
-    local difitems1=dif1
-    local difitems2=dif2
-    local difitems3=dif3
-    if (`difitems1' < `difitems2') {
-      local difitemsmin= `difitems1'
-      local difitemsmax= `difitems2'
-    }
-    else {
-      local difitemsmin= `difitems2'
-      local difitemsmax= `difitems1'
-    }
-    if (`difitems3' < `difitemsmin') {
-      local difitemsmid = `difitemsmin'
-      local difitemsmin= `difitems3'
-    }
-    else if (`difitems3' > `difitemsmax') {
-      local difitemsmid = `difitemsmax'
-      local difitemsmax= `difitems3'
-    }
-    else {
-      local difitemsmid = `difitems3'
-    }
-    local mod "gsem "
-    forvalues i=1/`nbitems' {
-      if (`i'==`difitemsmin' | `i'==`difitemsmax' | `i'==`difitemsmid') {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)"
-      }
-      else {
-        local mod = "`mod'"+"(1.item`i'<-THETA@1)"
-      }
-    }
-    local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
-    qui `mod'
-    mat V=r(table)
-    mat W=V[1..2,1...]
-    forvalues j=1/`nbitems' {
-      if (`j'<`difitemsmin') {
-        mat outmat[`k',`j'] = W[1,3*`j'] // items avant le premier dif
-      }
-      else if (`j'<`difitemsmid') {
-        mat outmat[`k',`j'] = W[1,1+3*`j'] // items après le premier dif
-      }
-      else if (`j'<`difitemsmax') {
-        mat outmat[`k',`j'] = W[1,2+3*`j'] // items après le deuxieme dif
-      }
-      else {
-        mat outmat[`k',`j'] = W[1,3+3*`j'] // items après le deuxieme dif
-      }
-    }
-    mat outmat[`k',`nbitems'+1] = W[1,3*`difitemsmin'-1] // coef de dif
-    mat outmat[`k',`nbitems'+2] = W[1,3*`difitemsmid'] // coef de dif
-    mat outmat[`k',`nbitems'+3] = W[1,3*`difitemsmax'+1] // coef de dif
-    mat outmat[`k',`nbitems'+4] = W[1,3*`nbitems'+4] // beta
-    mat outmat[`k',`nbitems'+5] = W[2,3*`nbitems'+4] // se beta
-    mat outmat[`k',`nbitems'+6] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',`nbitems'+7] = `difitemsmid' // numéro item de dif
-    mat outmat[`k',`nbitems'+8] = `difitemsmax' // numéro item de dif
-    restore
-  }
-  putexcel set "`path_res'/19`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}
-
-
-
-** Scenario 20: J = 7 items / M = 4 modalities / DIF size 0.5 x3
-local N = "100 200 300"
-foreach Nnn in `N' {
-local Nn =  `Nnn'
-local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
-local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/DIF/N`Nn'"
-local scenarios = "A B C D E F G"
-foreach scen in `scenarios' {
-clear
-import delim "`path_data'/scenario_20`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
-rename TT tt
-
-* Matrice de taille 1000 * 4 items + 1 DIF + beta + std beta + 1 dif
-local nbitems = 7
-local nbdif = 3
-local taillemat = 3*`nbitems'+9+2+`nbdif'
-mat outmat = J(1000,`taillemat',.)
-mat colnames outmat = "item1_1" "item1_2" "item1_3" "item2_1" "item2_2" "item2_3" "item3_1" "item3_2" "item3_3" "item4_1" "item4_2" "item4_3" "item5_1" "item5_2" "item5_3" "item6_1" "item6_2" "item6_3" "item7_1" "item7_2" "item7_3" "dif1_1" "dif1_2" "dif1_3" "dif2_1" "dif2_2" "dif2_3" "dif3_1" "dif3_2" "dif3_3" "beta" "se_beta" "dif_item_1" "dif_item_2" "dif_item_3"
-di "Scenario 20`scen' / N=`Nnn'"
-forvalues k=1/1000 {
-  if (mod(`k',100)==0) {
-    di "`k'/1000"
-  }
-  preserve
-  qui keep if replication==`k'
-  local difitems1=dif1
-  local difitems2=dif2
-  local difitems3=dif3
-  if (`difitems1' < `difitems2') {
-    local difitemsmin= `difitems1'
-    local difitemsmax= `difitems2'
-  }
-  else {
-    local difitemsmin= `difitems2'
-    local difitemsmax= `difitems1'
-  }
-  if (`difitems3' < `difitemsmin') {
-    local difitemsmid = `difitemsmin'
-    local difitemsmin= `difitems3'
-  }
-  else if (`difitems3' > `difitemsmax') {
-    local difitemsmid = `difitemsmax'
-    local difitemsmax= `difitems3'
-  }
-  else {
-    local difitemsmid = `difitems3'
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin') {
-      local constrnt = "constraint 1 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt2 = "constraint 2 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmax') {
-      local constrn3 = "constraint 3 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt4 = "constraint 4 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmid') {
-      local constrn5 = "constraint 5 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
-      local constrnt6 = "constraint 6 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
-    }
-  }
-  local mod "gsem "
-  forvalues i=1/`nbitems' {
-    if (`i'==`difitemsmin' | `i'==`difitemsmax' | `i'==`difitemsmid') {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1 tt)(2.item`i'<-THETA@2 tt)(3.item`i'<-THETA@3 tt)"
-    }
-    else {
-      local mod = "`mod'"+"(1.item`i'<-THETA@1)(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
-    }
-  }
-  local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(1 2 3 4 5 6)"
-  qui `constrnt'
-  qui `constrnt2'
-  qui `constrnt3'
-  qui `constrnt4'
-  qui `constrnt6'
-  qui `constrnt6'
-  qui `mod'
-  mat V=r(table)
-  mat W=V[1..2,1...]
-  forvalues j=1/`nbitems' {
-  if (`j'<`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+3] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+5] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+7] // items avant le premier dif
-      }
-  else if (`j'==`difitemsmin') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+4] // items du le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+7] // items du le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items du le premier dif    }
-    }
-  else if (`j'<`difitemsmid') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+6] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+8] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+10] // items avant le premier dif
-    }
-  else if (`j'==`difitemsmid') {
-      mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+7] // items avant le premier dif
-      mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+10] // items avant le premier dif
-      mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-    }
-  else if (`j'<`difitemsmax') {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+9] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+11] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+13] // items avant le premier dif
-  }
-  else if (`j'==`difitemsmax') {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+10] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+13] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+16] // items avant le premier dif
-  }
-  else {
-    mat outmat[`k',3*`j'-2] = W[1,7*(`j'-1)+12] // items avant le premier dif
-    mat outmat[`k',3*`j'-1] = W[1,7*(`j'-1)+14] // items avant le premier dif
-    mat outmat[`k',3*`j'] =   W[1,7*(`j'-1)+16] // items avant le premier dif
-  }
-  }
-    mat outmat[`k',3*`nbitems'+1] = W[1,7*(`difitemsmin'-1)+2] // coef de dif
-    mat outmat[`k',3*`nbitems'+2] = W[1,7*(`difitemsmin'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+3] = W[1,7*(`difitemsmin'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+4] = W[1,7*(`difitemsmid'-1)+5] // coef de dif
-    mat outmat[`k',3*`nbitems'+5] = W[1,7*(`difitemsmid'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+6] = W[1,7*(`difitemsmid'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+7] = W[1,7*(`difitemsmax'-1)+8] // coef de dif
-    mat outmat[`k',3*`nbitems'+8] = W[1,7*(`difitemsmax'-1)+11] // coef de dif
-    mat outmat[`k',3*`nbitems'+9] = W[1,7*(`difitemsmax'-1)+14] // coef de dif
-    mat outmat[`k',3*`nbitems'+10] = W[1,7*`nbitems'+10] // beta
-    mat outmat[`k',3*`nbitems'+11] = W[2,7*`nbitems'+10] // se beta
-    mat outmat[`k',3*`nbitems'+12] = `difitemsmin' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+13] = `difitemsmid' // numéro item de dif
-    mat outmat[`k',3*`nbitems'+14] = `difitemsmax' // numéro item de dif
-    restore
+*=================================================================================================================================================
+* Date : 2024-01-23
+* Stata version : Stata 18 SE
+*
+* This program analyses simulated data accounting for DIF through a partial credit model
+*
+* ado-files needed : - pcm, rosali (version 5.5 October 25, 2023, available on gitea)
+*
+*
+*================================================================================================================================================
+adopath+"/home/corentin/Documents/These/Recherche/ROSALI-SIM/Modules/rosali_custom"
+
+
+local N = "50 100 200 300"
+ local ss = "1 2 3 4 5 6 7 8 9 10 11 1 13 14 15 16 17 18 19 20"
+ foreach s in `ss' {
+ foreach Nnn in `N' {
+ local Nn =  `Nnn'
+ local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N`Nn'"
+ if (`s'<=4) {
+   local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N`Nn'"
+ }
+ local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/N`Nn'"
+ local scenarios = "A B C D E F G"
+ foreach scen in `scenarios' {
+ clear
+ import delim "`path_data'/scenario_`s'`scen'_`Nn'.csv", encoding(ISO-8859-2)  case(preserve) clear
+ rename TT tt
+
+ if (`s'<=2) {
+   local nbitems=4
+ }
+ else if (`s'<=4) {
+   local nbitems=7
+ }
+ else if (`s'<=12) {
+   local nbitems=4
+ }
+ else {
+   local nbitems=7
+ }
+
+if (mod(`s',2)==0) {
+  local nbmoda=3
+}
+else {
+  local nbmoda=1
+}
+
+ if (`s'<=4) {
+   local nbdif=0
+ }
+ else if (`s'<=8) {
+   local nbdif=1
+ }
+ else if (`s'<=16) {
+   local nbdif=2
+ }
+ else {
+   local nbdif=3
+ }
+ * taillemat = Maximum J*M cases pour les items par et J*M cases pour les dif par + J cases pour les DIF detect + nbdif cases pour dif réel
+ local taillemat=2*`nbitems'*`nbmoda'+`nbitems'+`nbdif'+2
+ local colna=""
+ forvalues i=1/`nbitems' {
+   forvalues z=1/`nbmoda' {
+     local colna = "`colna'"+"item`i'_`z' "
+     local colna = "`colna'"+"dif_`i'_`z' "
+   }
+ }
+ forvalues i=1/`nbitems' {
+   local colna = "`colna'"+"dif_detect_`i' "
+ }
+
+ forvalues i=1/`nbdif' {
+   local colna = "`colna'"+"real_dif_`i' "
+ }
+local colna = "`colna'" + "beta " + "se_beta"
+
+
+ mat outmat = J(1000,`taillemat',.)
+ mat colnames outmat= `colna'
+ di "Scenario `s'`scen' / N=`Nnn'"
+ forvalues k=1/1000 {
+   if (mod(`k',100)==0) {
+     di "`k'/1000"
+   }
+   preserve
+   qui keep if replication==`k'
+
+
+   * MERGE des modalités si non représentées
+
+   if (`nbmoda'>1 & `Nn'==50) {
+         local com_z = 0
+         qui gen comz = 0
+         forvalues j = 1 / `nbitems' {
+         local recoda_`j' = 0
+         qui tab item`j' if tt == 0, matrow(rect1_g0_`j') matcell(nbrt1_g0_`j')
+         local maxm`j'_t1_g0 = rect1_g0_`j'[r(r),1]
+         local minm`j'_t1_g0 = rect1_g0_`j'[1,1]
+
+         qui tab item`j' if tt == 1, matrow(rect1_g1_`j') matcell(nbrt1_g1_`j')
+         local minm`j'_t1_g1 = rect1_g1_`j'[1,1]
+         local maxm`j'_t1_g1 = rect1_g1_`j'[r(r),1]
+
+         local minm_`j' = min(`minm`j'_t1_g0',`minm`j'_t1_g1')
+         local maxm_`j' = max(`maxm`j'_t1_g0',`maxm`j'_t1_g1')
+         local nbm_`j' =  `=`maxm_`j''-`minm_`j'''
+
+         if `minm_`j'' != 0 & `com_z' == 0 {
+           local com_z = 1
+         }
+
+         qui count if item`j' == 3 & tt == 0
+         local mod3plac = r(N)
+         qui count if item`j' == 3 & tt == 1
+         local mod3tt = r(N)
+         local nb_rn3 = min(`mod3plac',`mod3tt')
+         if `nb_rn3'==0 {
+           qui replace comz = 1
+         }
+
+         forvalues m = 0/`=`nbm_`j''-1' {
+           qui count if item`j' == `m' & tt == 0
+           local nb_rn1_g0 = r(N)
+           qui count if item`j' == `m' & tt == 1
+           local nb_rn1_g1 = r(N)
+           local nb_rn = min(`nb_rn1_g0',`nb_rn1_g1')
+           if `nb_rn' == 0 {
+             qui replace comz = 1
+             local recoda_`j' = 1
+             if  `m' == 0 | `m' < `minm`j'_t1_g0' | `m' < `minm`j'_t1_g1' {
+               local stop = 1
+               forvalues kk = 1/`=`nbm_`j''-`m'' {
+                 qui count if item`j' == `=`m' + `kk'' & tt == 0
+                 local v`kk'1_0 = r(N)
+                 qui count if item`j' == `=`m' + `kk'' & tt == 1
+                 local v`kk'1_1 = r(N)
+                 if (`v`kk'1_0' != 0 | `v`kk'1_1' != 0) & `stop' != 0 {
+                   qui replace item`j'= `=`m'+`kk'' if item`j'==`m'
+                   local zzz=`j'+`nbitems'
+                   *qui replace item`zzz'=`=`m'+`kk'' if item``=`j'+`nbitems'''==`m'
+                   *di  "WARNING SCENARIO `k': items `j': answers `m' and `=`m'+`kk'' merged"
+                   local stop = 0
+                 }
+               }
+             }
+             else if `m' == `=`nbm_`j''-1' | `m' >= `maxm`j'_t1_g1' {
+               local stop = 1
+               forvalues kk = 1/`=`m'' {
+                 qui count if item`j' == `=`m' - `kk'' & tt == 0
+                 local v`kk'1_0 = r(N)
+                 qui count if item`j' == `=`m' - `kk'' & tt == 1
+                 local v`kk'1_1 = r(N)
+                 if (`v`kk'1_0' != 0 | `v`kk'1_1' != 0) & `stop' != 0 {
+                   qui replace item`j'= `=`m' - `kk'' if item`j'==`m'
+                   local zzz=`j'+`nbitems'
+                   *qui replace item`zzz'= `=`m' - `kk'' if item`zzz'==`m'
+                   *di  "WARNING SCENARIO `k': items `j': answers `m' and `=`m'+`kk'' merged"
+                   local stop = 0
+                 }
+               }
+             }
+             else {
+               if runiform()>0.5{
+                 local stop = 1
+                 forvalues kk = 1/`m' {
+                   qui count if item`j' == `=`m' - `kk'' & tt == 0
+                   local v`kk'1_0 = r(N)
+                   qui count if item`j' == `=`m' - `kk'' & tt == 1
+                   local v`kk'1_1 = r(N)
+                   if (`v`kk'1_0' != 0 | `v`kk'1_1' != 0) & `stop' != 0 {
+                     qui replace item`j'= `=`m'-`kk'' if item`j'==`m'
+                     local zzz=`j'+`nbitems'
+                     *qui replace item`zzz'=`=`m'-`kk'' if item``=`j'+`nbitems'''==`m'
+                     *di  "WARNING SCENARIO `k': items `j': answers `m' and `=`m'+`kk'' merged"
+                     local stop = 0
+                   }
+                 }
+               }
+               else {
+                 local stop = 1
+                 forvalues kk = 1/`=`nbm_`j''-`m'' {
+                   qui count if item`j' == `=`m' + `kk'' & tt == 0
+                   local v`kk'1_0 = r(N)
+                   qui count if item`j' == `=`m' + `kk'' & tt == 1
+                   local v`kk'1_1 = r(N)
+                   if (`v`kk'1_0' != 0 | `v`kk'1_1' != 0) & `stop' != 0{
+                     qui replace item`j'=`=`m' + `kk'' if item`j'==`m'
+                     local zzz=`j'+`nbitems'
+                     *qui replace item`zzz'=`=`m' + `kk'' if item``=`j'+`nbitems'''==`m'
+                     *di  "WARNING SCENARIO `k': items `j': answers `m' and `=`m'+`kk'' merged"
+                     local stop = 0
+                   }
+                   else {
+                     if `stop' != 0 {
+                       qui replace item`j'= `nbm_`j'' if item`j'==`m'
+                       local zzz=`j'+`nbitems'
+                       *qui replace item`zzz'= `nbm_`j'' if item``=`j'+`nbitems'''==`m'
+                       *di  "WARNING SCENARIO `k': items `j': answers `m' and `=`m'+`kk'' merged"
+                       local stop = 0
+                     }
+                   }
+                 }
+               }
+             }
+           }
+         }
+         qui levelsof item`j'
+         local val = r(levels)
+         local checker: word 1 of `val'
+         local checker2: word 2 of `val'
+         local checker3: word 3 of `val'
+         local nummoda=r(r)
+         local nbmoda_`j'=`nummoda'
+         if (`nummoda'==2) {
+           qui recode item`j' (`checker'=0) (`checker2'=1)
+         }
+         if (`nummoda'==3) {
+         if (`checker'!=0) {
+           qui recode item`j' (`checker'=0) (`checker2'=1) (`checker3'=2)
+         }
+         else if (`checker2'!=1) {
+           qui recode item`j' (`checker2'=1) (`checker3'=2)
+         }
+         else if (`checker3'!=2) {
+           qui recode item`j' (`checker3'=2)
+         }
+       }
+     }
+
+     qui valuesof comz
+     local val = r(values)
+     local checker: word 1 of `val'
+   }
+   else {
+     forvalues jj=1/`nbitems' {
+       local nbmoda_`jj'=`nbmoda'
+     }
+   }
+
+
+   * ROSALI
+   qui rosali_original item1-item`nbitems' item1-item`nbitems', group(tt)
+   qui mat resmat=r(difitems)
+   local nbitems2 = 2*`nbitems'
+
+   * Calculer le nbre d'items détectés
+   local nbdetect = 0
+   local stop = 0
+   forvalues jj=1/`nbitems' {
+       if (`stop'==0) {
+         mat testm=J(1,1,.)
+         if (resmat[1,`jj']==testm[1,1]) {
+           local stop = 1
+           local nbdetect = `jj'-1
+         }
+       }
+   }
+
+   * Stocker les items détectés +
+   * Définition des contraintes
+   local csrt=0
+   mat testm=J(1,1,0)
+   forvalues u=1/`nbdetect' {
+      local difitems`u'=resmat[1,`u']
+       local i=`difitems`u''
+        if (`nbmoda_`i''==3 & resmat[1,`nbitems'+`i']!=testm[1,1]){
+         local constrnt`u' = "constraint `u' 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
+         qui `constrnt`u''
+         local v=`u'+100
+         local constrnt`u'_2 = "constraint `v' 3*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([3.item`i']_cons-([3.item`i']_cons+[3.item`i'] tt))"
+         qui `constrnt`u'_2'
+        }
+        if (`nbmoda_`i''==2 & resmat[1,`nbitems'+`i']!=testm[1,1]){
+         local constrnt`u' = "constraint `u' 2*([1.item`i']_cons-([1.item`i']_cons+[1.item`i'] tt))=([2.item`i']_cons-([2.item`i']_cons+[2.item`i'] tt))"
+         qui `constrnt`u''
+        }
+       }
+
+   * Définition du modèle
+   local mod "gsem "
+   local conformula = ""
+   forvalues i=1/`nbitems' {
+       local mod = "`mod'"+"(1.item`i'<-THETA@1)"
+       if (`nbmoda_`i''==3) {
+         local mod = "`mod'"+"(2.item`i'<-THETA@2)(3.item`i'<-THETA@3)"
+       }
+       else if (`nbmoda_`i''==2) {
+         local mod = "`mod'"+"(2.item`i'<-THETA@2)"
+       }
+   }
+   forvalues u=1/`nbdetect' {
+       local v=`difitems`u''
+       local mod = "`mod'"+"(1.item`v'<-THETA@1 tt)"
+       if (`nbmoda_`v''==3) {
+         local mod = "`mod'"+"(2.item`v'<-THETA@2 tt)(3.item`v'<-THETA@3 tt)"
+       }
+       else if (`nbmoda_`v''==2) {
+         local mod = "`mod'"+"(2.item`v'<-THETA@2 tt)"
+       }
+       local w= 100+`u'
+       if (resmat[1,`nbitems'+`v']!=testm[1,1] & `nbmoda_`v''==3) {
+         local conformula = "`conformula'" + "`u' " + "`w' "
+       }
+       else if (resmat[1,`nbitems'+`v']!=testm[1,1] & `nbmoda_`v''==2) {
+         local conformula = "`conformula'" + "`u' "
+       }
+   }
+   if ("`conformula'" != "") {
+     local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent constraint(`conformula')"
+   }
+   else {
+     local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
+   }
+   *calcul du modèle
+   qui `mod'
+   mat V=r(table)
+   mat W=V[1..2,1...]
+
+   * compilation
+   forvalues j=1/`nbitems' {
+     forvalues z=1/`nbmoda_`j'' {
+       mat outmat[`k',colnumb(outmat,"item`j'_`z'")] = W[1,colnumb(W,"`z'.item`j':_cons")]
+     }
+   }
+   * compilation DIF
+   forvalues u=1/`nbdetect' {
+     local j=`difitems`u''
+       forvalues z=1/`nbmoda_`j'' {
+         mat outmat[`k',colnumb(outmat,"dif_`u'_`z'")] = W[1,colnumb(W,"`z'.item`j':tt")]
+         mat outmat[`k',colnumb(outmat,"dif_detect_`u'")] = `j'
+       }
+     }
+
+   * Stocker les items de DIF originaux
+   if (`nbdif' > 0) {
+     qui levelsof dif1
+     local ldif1 = r(levels)
+     local diff1: word 1 of `ldif1'
+     qui mat outmat[`k',colnumb(outmat,"real_dif_1")]=`diff1'
+     if (`nbdif' > 1) {
+       qui levelsof dif2
+       local ldif2 = r(levels)
+       local diff2: word 1 of `ldif2'
+       qui mat outmat[`k',colnumb(outmat,"real_dif_2")]=`diff2'
+       if (`nbdif' > 2) {
+         qui levelsof dif3
+         local ldif3 = r(levels)
+         local diff3: word 1 of `ldif3'
+         qui mat outmat[`k',colnumb(outmat,"real_dif_3")]=`diff3'
+       }
+     }
+   }
+   qui mat outmat[`k',colnumb(outmat,"beta")]=W[1,colnumb(W,"THETA:tt")]
+   qui mat outmat[`k',colnumb(outmat,"se_beta")]=W[2,colnumb(W,"THETA:tt")]
+   restore
+ }
+ putexcel set "`path_res'/`s'`scen'_`Nn'_original.xls", sheet("outmat") replace
+ putexcel A1=matrix(outmat), colnames
 }
-putexcel set "`path_res'/20`scen'_`Nn'.xls", sheet("outmat") replace
-putexcel A1=matrix(outmat), colnames
 }
 }
diff --git a/Scripts/Analysis/DIF/temp/item_merger.do b/Scripts/Analysis/DIF/merger/item_merger.do
similarity index 100%
rename from Scripts/Analysis/DIF/temp/item_merger.do
rename to Scripts/Analysis/DIF/merger/item_merger.do