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Created ROSALI screening version

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Corentin Choisy
2025-02-13 15:24:10 +01:00
parent 7712f8396f
commit f04322a9db
8 changed files with 3751 additions and 49 deletions
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1366
Modules/rosali_custom/rosali_nolrt_anchor.ado Normal file
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Modules/rosali_custom/rosali_nolrt_screening.ado Normal file
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RProject/Scripts/Analysis/aggregation.R
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@ -147,19 +147,35 @@ replicate_pcm_analysis<- function(df=NULL,treatment='TT',irtmodel='PCM2',method=
#### Create data.frame
#results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
#results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
#results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
#results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
#results <- c(results,results2)
results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
results <- c(sapply(c("050",100,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
results2 <- c(sapply(c("050",100,300),function(x) paste0(results2,'_',x)))
results <- sort(results)
results2 <- sort(results2)
results <- c(results,results2)
results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
)
results <- gsub('050',"50",results)
# results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
# sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
# )
#### Compiler function
compile_simulation <- function(scenario) {
@ -302,21 +318,21 @@ res.dat[is.nan(res.dat)] <- NA
#### Create data.frame
results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
results <- c(sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
results <- c(sapply(c("050",100,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
results2 <- c(sapply(c("050",100,300),function(x) paste0(results2,'_',x)))
results <- sort(results)
results2 <- sort(results2)
results <- c(results,results2)
results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
)
results <- results[19:length(results)]
results <- gsub('050',"50",results)
#### Compiler function
@ -425,19 +441,23 @@ res.dat.dif$bias <- res.dat.dif$eff.size-res.dat.dif$m.beta
#### Create data.frame
results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
results <- c(sapply(c("050",100,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
results2 <- c(sapply(c("050",100,300),function(x) paste0(results2,'_',x)))
results <- sort(results)
results2 <- sort(results2)
results <- c(results,results2)
results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
)
results <- gsub('050',"50",results)
#### Compiler function
@ -719,19 +739,36 @@ res.dat.dif.rosali$bias <- res.dat.dif.rosali$eff.size-res.dat.dif.rosali$m.beta
#### Create data.frame
#results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
#results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
#results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
#results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
#results <- c(results,results2)
#results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
# sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
#)
results <- c(sapply(c(2,4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
results <- c(sapply(c("050",100,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
results2 <- c(sapply(c("050",100,300),function(x) paste0(results2,'_',x)))
results <- sort(results)
results2 <- sort(results2)
results <- c(results,results2)
results <- c(sapply(1:16,function(x) c(results[x],results[x+16],results[x+32])),
sapply(1:30,function(x) c(results[x+48],results[x+30+48],results[x+60+48]))
)
results <- gsub('050',"50",results)
#### Compiler function
@ -985,6 +1022,7 @@ res.dat.dif.resali[substr(res.dat.dif.resali$scenario,1,2)%in%seq(10,16,2),'nb.d
res.dat.dif.resali[substr(res.dat.dif.resali$scenario,1,2)%in%seq(18,20,2),'nb.dif'] <- 3
res.dat.dif.resali[res.dat.dif.resali$N==50,"dif.size"] <- res.dat.dif.resali[which(res.dat.dif.resali$N==50)+1,"dif.size"]
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="B",]$eff.size <- 0.2
res.dat.dif.resali[res.dat.dif.resali$scenario=="20E" & res.dat.dif.resali$N==50,]$dif.size <- -0.5
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="C" & res.dat.dif.resali$dif.size==0,]$eff.size <- 0.4
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="C" & res.dat.dif.resali$dif.size!=0,]$eff.size <- 0.2
res.dat.dif.resali[res.dat.dif.resali$scenario.type=="D" & res.dat.dif.resali$dif.size!=0,]$eff.size <- 0.4
@ -1203,7 +1241,8 @@ res.dat.article.rosali.2$bias <- -1*res.dat.article.rosali.2$bias
res.dat.article.rosali.2.nodif <- res.dat.article.rosali.2[res.dat.article.rosali.2$nb.dif==0,]
# STRATEGY 3 - RESIDIF
res.dat.dif.resali[1,"N"] <- 50
res.dat.dif.resali$dif.size <- res.dat.dif.rosali$dif.size
res.dat.article.residif <- res.dat.dif.resali[,c("N","J","eff.size","nb.dif","dif.size",
"m.beta","bias","true.value.in.ci.p","h0.rejected.p",
"theoretical.power")]
@ -1219,7 +1258,7 @@ res.dat.article.residif[res.dat.article.residif$nb.dif==0,"true.gamma"] <- NA
res.dat.article.residif[is.na(res.dat.article.residif)] <- " "
res.dat.article.residif$bias <- -1*res.dat.article.residif$bias
res.dat.article.residif <- reshape(res.dat.article.residif,
direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N" )
direction = "wide", idvar = c("J","true.beta","nb.dif",'true.gamma'),timevar = "N")
res.dat.article.residif.dif <- res.dat.article.residif[res.dat.article.residif$nb.dif>0,]
write.csv(res.dat.article.residif.dif,"/home/corentin/Documents/These/Valorisation/Articles/Simulations 1/Tables/res_RESIDIF_DIF.csv")
res.dat.article.residif.nodif <- res.dat.article.residif[res.dat.article.residif$nb.dif==0,]
@ -1240,6 +1279,7 @@ res.dat.article.residif.2[res.dat.article.residif.2$nb.dif==0,"true.gamma"] <- N
res.dat.article.residif.2[is.na(res.dat.article.residif.2)] <- " "
res.dat.article.residif.2$bias <- -1*res.dat.article.residif.2$bias
res.dat.article.residif.2.nodif <- res.dat.article.residif.2[res.dat.article.residif.2$nb.dif==0,]
res.dat.article.residif.dif
# STRATEGY 4 - PERFECT-DIF

25
RProject/Scripts/Analysis/functions/resali.R
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@ -27,10 +27,9 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
for (i in items) {
dat[,paste0('res_',i)] <- IRT.residuals(pcm_initial)$stand_residuals[,i]
res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
pval[i] <- res.anova[[i]][1,"Pr(>F)"]
fval[i] <- res.anova[[i]][1,'F value']
pval[c(i,i+nbitems)] <- c(res.anova[[i]][1,"Pr(>F)"],res.anova[[i]][3,"Pr(>F)"])
fval[c(i,i+nbitems)] <- c(res.anova[[i]][1,'F value'],res.anova[[i]][3,"F value"])
}
print(res.anova)
if (verbose) {
cat('DONE\n')
cat('-----------------------------------------------------------\n')
@ -44,9 +43,10 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
cat(paste('COMPUTING STEP',k,'\n'))
cat('-----------------------------------------------------------\n')
}
res.item <- gsub("[a-z]", "",colnames(resp)[which.max(fval)])
numitem <- ifelse(which.max(fval)%%(length(fval)/2)!=0,which.max(fval)%%(length(fval)/2),length(fval)/2)
res.item <- gsub("[a-z]", "",colnames(resp)[numitem])
res.items <- c(res.items,res.item)
res.uni <- res.anova[[which.max(fval)]][3,"Pr(>F)"]>0.05
res.uni <- res.anova[[numitem]][3,"Pr(>F)"]>0.05
res.uniform <- c(res.uniform,res.uni)
items_n <- c(items_n[items_n!=paste0('item',res.item)],paste0("item",res.item,c("noTT","TT")))
dat[dat$TT==1,paste0("item",res.item,'TT')] <- dat[dat$TT==1,paste0('item',res.item)]
@ -54,24 +54,19 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
resp <- dat[,items_n]
grp <- dat[,group]
pcm_while <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
nbitems <- length(items_n)
nbitems <- length(items_n)-2*length(res.items)
res.anova <- rep(NA,nbitems)
pval <- rep(NA,nbitems)
fval <- rep(NA,nbitems)
pval <- rep(NA,2*nbitems)
fval <- rep(NA,2*nbitems)
for (i in 1:nbitems) {
dat[,paste0('res_',i)] <- IRT.residuals(pcm_while)$stand_residuals[,i]
res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
pval[i] <- res.anova[[i]][1,"Pr(>F)"]
pval[i+nbitems] <- res.anova[[i]][3,"Pr(>F)"]
fval[i] <- res.anova[[i]][1,'F value']
fval[i+nbitems] <- res.anova[[i]][3,"F value"]
}
zz <- 0
for (name_i in items_n) {
zz <- zz+1
if (grepl("TT",name_i)) {
pval[zz] <- 1
fval[zz] <- 0
}
}
if (verbose) {
cat('DONE\n')
cat('-----------------------------------------------------------\n')

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RProject/Scripts/Analysis/functions/resali_v2.R Normal file
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@ -0,0 +1,167 @@
library(TAM)
resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
if (verbose) {
cat('-----------------------------------------------------------\n')
cat('COMPUTING INITIAL PCM\n')
cat('-----------------------------------------------------------\n')
}
nbitems <- length(items)
nbitems_o <- nbitems
items_n <- paste0('item',items)
resp <- df[,items_n]
grp <- df[,group]
pcm_initial <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
dat <- df
dat$score <- rowSums(dat[,items_n])
nqt <- ifelse(length(unique(quantile(dat$score,seq(0,1,0.2))))==6,5,length(unique(quantile(dat$score,seq(0,1,0.2))))-1)
while (length(unique(quantile(dat$score,seq(0,1,1/nqt))))!=nqt+1) {
nqt <- nqt-1
}
# ITEM POLYTOMIQUE
if (max(resp)>1) {
dat$score_q5 <- cut(dat$score,unique(quantile(dat$score,seq(0,1,1/nqt))),labels=1:nqt,include.lowest=T)
res.anova <- rep(NA,nbitems)
pval <- rep(NA,nbitems)
fval <- rep(NA,nbitems)
for (i in items) {
dat[,paste0('res_',i)] <- IRT.residuals(pcm_initial)$stand_residuals[,i]
res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
pval[i] <- res.anova[[i]][1,"Pr(>F)"]
fval[i] <- res.anova[[i]][1,'F value']
}
print(res.anova)
if (verbose) {
cat('DONE\n')
cat('-----------------------------------------------------------\n')
}
res.items <- c()
res.uniform <- c()
k <- 1
while(any(pval<0.05/(nbitems_o*3))) {
k <- k+1
if (verbose) {
cat(paste('COMPUTING STEP',k,'\n'))
cat('-----------------------------------------------------------\n')
}
res.item <- gsub("[a-z]", "",colnames(resp)[which.max(fval)])
res.items <- c(res.items,res.item)
res.uni <- res.anova[[which.max(fval)]][3,"Pr(>F)"]>0.05
res.uniform <- c(res.uniform,res.uni)
items_n <- c(items_n[items_n!=paste0('item',res.item)],paste0("item",res.item,c("noTT","TT")))
dat[dat$TT==1,paste0("item",res.item,'TT')] <- dat[dat$TT==1,paste0('item',res.item)]
dat[dat$TT==0,paste0("item",res.item,'noTT')] <- dat[dat$TT==0,paste0('item',res.item)]
resp <- dat[,items_n]
grp <- dat[,group]
pcm_while <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
nbitems <- length(items_n)
res.anova <- rep(NA,nbitems)
pval <- rep(NA,nbitems)
fval <- rep(NA,nbitems)
for (i in 1:nbitems) {
dat[,paste0('res_',i)] <- IRT.residuals(pcm_while)$stand_residuals[,i]
res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT*score_q5,data=dat))
pval[i] <- res.anova[[i]][1,"Pr(>F)"]
fval[i] <- res.anova[[i]][1,'F value']
}
zz <- 0
for (name_i in items_n) {
zz <- zz+1
if (grepl("TT",name_i)) {
pval[zz] <- 1
fval[zz] <- 0
}
}
if (verbose) {
cat('DONE\n')
cat('-----------------------------------------------------------\n')
}
}
if (verbose) {
cat("DETECTED DIF ITEMS\n")
cat('-----------------------------------------------------------\n')
}
if (length(res.items>0)) {
results <- data.frame(dif.items=res.items,
uniform=1*res.uniform)
return(results)
}
else {
if (verbose) {
cat("No DIF was detected\n")
}
return(NULL)
}
# ITEM DICHOTOMIQUE
} else {
res.anova <- rep(NA,nbitems)
pval <- rep(NA,nbitems)
fval <- rep(NA,nbitems)
for (i in items) {
dat[,paste0('res_',i)] <- IRT.residuals(pcm_initial)$stand_residuals[,i]
res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT,data=dat))
pval[i] <- res.anova[[i]][1,"Pr(>F)"]
fval[i] <- res.anova[[i]][1,'F value']
}
if (verbose) {
cat('DONE\n')
cat('-----------------------------------------------------------\n')
}
res.items <- c()
k <- 1
while(any(pval<0.05/(nbitems_o))) {
k <- k+1
if (verbose) {
cat(paste('COMPUTING STEP',k,'\n'))
cat('-----------------------------------------------------------\n')
}
res.item <- gsub("[a-z]", "",colnames(resp)[which.max(fval)])
res.items <- c(res.items,res.item)
items_n <- c(items_n[items_n!=paste0('item',res.item)],paste0("item",res.item,c("noTT","TT")))
dat[dat$TT==1,paste0("item",res.item,'TT')] <- dat[dat$TT==1,paste0('item',res.item)]
dat[dat$TT==0,paste0("item",res.item,'noTT')] <- dat[dat$TT==0,paste0('item',res.item)]
resp <- dat[,items_n]
grp <- dat[,group]
pcm_while <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
nbitems <- length(items_n)
res.anova <- rep(NA,nbitems)
pval <- rep(NA,nbitems)
fval <- rep(NA,nbitems)
for (i in 1:nbitems) {
dat[,paste0('res_',i)] <- IRT.residuals(pcm_while)$stand_residuals[,i]
res.anova[i] <- summary(aov(dat[,paste0('res_',i)]~TT,data=dat))
pval[i] <- res.anova[[i]][1,"Pr(>F)"]
fval[i] <- res.anova[[i]][1,'F value']
}
zz <- 0
for (name_i in items_n) {
zz <- zz+1
if (grepl("TT",name_i)) {
pval[zz] <- 1
fval[zz] <- 0
}
}
if (verbose) {
cat('DONE\n')
cat('-----------------------------------------------------------\n')
}
}
if (verbose) {
cat("DETECTED DIF ITEMS\n")
cat('-----------------------------------------------------------\n')
}
if (length(res.items>0)) {
results <- data.frame(dif.items=res.items,
uniform=rep(1,length(res.items)))
return(results)
}
else {
if (verbose) {
cat("No DIF was detected\n")
}
return(NULL)
}
}
}

35
RProject/Scripts/Analysis/resali_analysis.R
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@ -113,15 +113,18 @@ generate_resali <- function(scenario=NULL,grp=NULL) {
return(df_res)
}
#results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
#results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
#results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
#results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
results <- c(sapply(c(2:4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
results <- sort(results)
@ -144,13 +147,27 @@ for (r in results) {
## Liste des scenarios
results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
#results <- c(sapply(1:4,function(x) paste0(x,c('A','B','C','D','E'))),sapply(5:9,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
#results2 <- c(sapply(10:20,function(x) paste0(x,c('A','B','C','D','E','F','G'))))
results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
#results <- c(sapply(c(50,100,200,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
#results2 <- c(sapply(c(50,100,200,300),function(x) paste0(results2,'_',x)))
#results <- sort(results)
#results2 <- sort(results2)
#results <- c(results,results2)
results <- c(sapply(c(2:4),function(x) paste0(x,c('A','B','C'))),sapply(c(6,8),function(x) paste0(x,c('A','B','C','D','E'))))
results2 <- c(sapply(seq(10,20,2),function(x) paste0(x,c('A','B','C','D','E'))))
results <- c(sapply(c(50,100,300),function(x) paste0(results,'_',x)))
results2 <- c(sapply(c(50,100,300),function(x) paste0(results2,'_',x)))
results <- sort(results)

375
Scripts/Analysis/DIF-RESIDUALS/pcm_dif_residus2.do Normal file
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@ -0,0 +1,375 @@
*=================================================================================================================================================
* 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 = "50 100 300"
local ss = "18 20"
foreach s in `ss' {
foreach Nnn in `N' {
local Nn = `Nnn'
local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Detection_data"
local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N`Nn'"
local scenarios = "A B C D E"
if (`s' <= 4) {
local scenarios = "A B C"
}
foreach scen in `scenarios' {
clear
import delim "`path_data'/`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
if (mod(`s',2)==0) {
local taillemat=2*`nbitems'*`nbmoda'+`nbitems'+`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' {
if (mod(`s',2)==1) {
local colna = "`colna'"+"dif_detect_`i' "
}
if (mod(`s',2)==0) {
local colna = "`colna'"+"dif_detect_`i' "+"dif_detect_unif_`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'-1
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'
}
}
local nbitems2 = 2*`nbitems'
* Calculer le nbre d'items détectés
local nbdetect = 0
local stop = 0
forvalues jj=1/`nbitems' {
qui levelsof dif_detect_`jj'
local detected=r(levels)
if (`stop'==0) {
mat testm=J(1,1,.)
if (`detected'==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' {
qui levelsof dif_detect_`u'
local detected=r(levels)
local difitems`u'=`detected'
local i=`difitems`u''
qui levelsof dif_detect_unif_`u'
local detected_unif=r(levels)
if (`nbmoda_`i''==3 & `detected_unif'!=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 & `detected_unif'!=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'
qui levelsof dif_detect_unif_`u'
local detected=r(levels)
local unif_`u'=r(levels)
if (`detected'!=testm[1,1] & `nbmoda_`v''==3) {
local conformula = "`conformula'" + "`u' " + "`w' "
}
else if (`detected'!=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'
if (mod(`s',2)==0) {
mat outmat[`k',colnumb(outmat,"dif_detect_unif_`u'")] = `unif_`u''
}
}
* 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
}
}
}

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*=================================================================================================================================================
* 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/Simulations/Modules/rosali_custom"
local N = "50 100 200 300"
local ss = "2 4 8 12 16 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-IMPROVED/MIMIC-NOLRT/N`Nn'"
local path_log = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/log/"
local scenarios = "A B C D E"
if (`s' <= 4) {
local scenarios = "A B C"
}
foreach scen in `scenarios' {
clear
import delim "`path_data'/scenario_`s'`scen'_`Nn'.csv", encoding(ISO-8859-2) case(preserve) clear
rename TT tt
log using "`path_log'/log_`s'`scen'_`Nn'.log", replace
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+1
if (mod(`s',2)==0) {
local taillemat=2*`nbitems'*`nbmoda'+`nbitems'+`nbitems'+`nbdif'+2+1
}
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' {
if (mod(`s',2)==1) {
local colna = "`colna'"+"dif_detect_`i' "
}
if (mod(`s',2)==0) {
local colna = "`colna'"+"dif_detect_`i' "+"dif_detect_unif_`i' "
}
}
forvalues i=1/`nbdif' {
local colna = "`colna'"+"real_dif_`i' "
}
local colna = "`colna'" + "beta " + "se_beta " + "lrt_passed"
mat outmat = J(1000,`taillemat',.)
mat colnames outmat= `colna'
di "Scenario `s'`scen' / N=`Nnn'"
forvalues k=1/1000 {
di "###################################################################################"
di "###################################################################################"
di "###################################################################################"
di "Scenario `s'`scen' N=`Nn' ########## `k'/1000"
di "###################################################################################"
di "###################################################################################"
di "###################################################################################"
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'-1
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
rosali_nolrt_screening item1-item`nbitems' item1-item`nbitems', group(tt)
qui mat resmat=r(difitems)
local nbitems2 = 2*`nbitems'
mat lrt_passed = resmat[1,`nbitems2'+1]
* 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'
local unif_`u'=0
if (resmat[1,`nbitems'+`v']!=testm[1,1] & `nbmoda_`v''==3) {
local conformula = "`conformula'" + "`u' " + "`w' "
local unif_`u'=1
}
else if (resmat[1,`nbitems'+`v']!=testm[1,1] & `nbmoda_`v''==2) {
local conformula = "`conformula'" + "`u' "
local unif_`u'=1
}
}
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
`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'
if (mod(`s',2)==0) {
mat outmat[`k',colnumb(outmat,"dif_detect_unif_`u'")] = `unif_`u''
}
}
* 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")]
qui mat outmat[`k',colnumb(outmat,"lrt_passed")]=lrt_passed[1,1]
restore
}
log close
putexcel set "`path_res'/`s'`scen'_`Nn'_original.xls", sheet("outmat") replace
putexcel A1=matrix(outmat), colnames
}
}
}