diff --git a/RProject/Scripts/aggregation.R b/RProject/Scripts/aggregation.R
index 41b1c20..ffa4915 100644
--- a/RProject/Scripts/aggregation.R
+++ b/RProject/Scripts/aggregation.R
@@ -629,24 +629,39 @@ results <- c(results,results2)
 compile_simulation2_resali <- function(scenario) {
   name <- as.numeric(gsub("[^0-9.-]", "", substr(scenario,start=0,stop=2)))
   if (substr(scenario,start=nchar(scenario)-1,stop=nchar(scenario))=="50" & name>0) {
-    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N50/',scenario,'_original.xls'))
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N50/',scenario,'_original.xls'))
   }
   if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="100" & name>0) {
-    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N100/',scenario,'_original.xls'))
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N100/',scenario,'_original.xls'))
   }
   if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="200" & name>0) {
-    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N200/',scenario,'_original.xls'))
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N200/',scenario,'_original.xls'))
   }
   if (substr(scenario,start=nchar(scenario)-2,stop=nchar(scenario))=="300" & name>0) {
-    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/resali-DIF/N300/',scenario,'_original.xls'))
+    s <- read_excel(paste0('/home/corentin/Documents/These/Recherche/Simulations/Analysis/RESALI/Results/N300/',scenario,'_original.xls'))
   }
   J <- max(which(sapply(1:7,function(x) paste0('item',x) %in% colnames(s) | paste0('item',x,'_1') %in% colnames(s))))
   M <- 1+sum(sapply(1:3,function(x) paste0('item1_',x) %in% colnames(s) ))
   if (M==1) {M <- 2}
-  nb.dif <- max(which(sapply(1:3,function(x) paste0('dif',x) %in% colnames(s) | paste0('dif',x,'_1') %in% colnames(s))))
+  nb.dif.true <- ifelse(name<=4,0,ifelse(name<=8,1,ifelse(name<=16,2,3)))
+  if (name %in% c(3,4,13:20)) {
+    m.nb.dif.detect <- mean(ifelse(is.na(s$dif_1_1),0,
+                                   ifelse(is.na(s$dif_2_1),1,
+                                          ifelse(is.na(s$dif_3_1),2,
+                                                 ifelse(is.na(s$dif_4_1),3,
+                                                        ifelse(is.na(s$dif_5_1),4,
+                                                               ifelse(is.na(s$dif_6_1),5,
+                                                                      ifelse(is.na(s$dif_7_1),6,7))))))))
+  }
+  if (!(name %in% c(3,4,13:20))) {
+    m.nb.dif.detect <- mean(ifelse(is.na(s$dif_1_1),0,
+                                   ifelse(is.na(s$dif_2_1),1,
+                                          ifelse(is.na(s$dif_3_1),2,
+                                                 ifelse(is.na(s$dif_4_1),3,4)))))
+  }
   if (J==4) {
     if (M==2) {
-      a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4))
+      a <- data.frame(m.item1=mean(s$item1_1),m.item2=mean(s$item2_1),m.item3=mean(s$item3_1),m.item4=mean(s$item4_1))
     } else {
       a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
                       m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
@@ -656,8 +671,8 @@ compile_simulation2_resali <- function(scenario) {
     }
   } else {
     if (M==2) {
-      a <- data.frame(m.item1=mean(s$item1),m.item2=mean(s$item2),m.item3=mean(s$item3),m.item4=mean(s$item4),
-                      m.item5=mean(s$item5),m.item6=mean(s$item6),m.item7=mean(s$item7))
+      a <- data.frame(m.item1=mean(s$item1_1),m.item2=mean(s$item2_1),m.item3=mean(s$item3_1),m.item4=mean(s$item4_1),
+                      m.item5=mean(s$item5_1),m.item6=mean(s$item6_1),m.item7=mean(s$item7_1))
     } else {
       a <- data.frame(m.item1_1=mean(s$item1_1),m.item1_2=mean(s$item1_2),m.item1_3=mean(s$item1_3),
                       m.item2_1=mean(s$item2_1),m.item2_2=mean(s$item2_2),m.item2_3=mean(s$item2_3),
@@ -679,12 +694,106 @@ compile_simulation2_resali <- function(scenario) {
                   J=J,
                   M=M,
                   eff.size=eff.size,
-                  nb.dif=nb.dif,
+                  nb.dif=nb.dif.true,
+                  m.nb.dif.detect=m.nb.dif.detect,
                   dif.size=dif.size
   )
   true.value.in.ci <- eff.size <= s$beta+1.96*s$se_beta & eff.size >= s$beta-1.96*s$se_beta
   beta.same.sign.truebeta.p <- ifelse(rep(eff.size,nrow(s))==0,NA,(rep(eff.size,nrow(s))/s$beta)>0)
   num.reject <- which((s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0)
+  dif.d <- mean(sapply(1:1000,function(x) any(!is.na(s[x,paste0("dif_",1:unique(b$J),"_1")]))))
+  if (nb.dif.true==0) {
+    prop.perfect <- NA
+    flexible.detect <- NA
+    moreflexible.detect <- NA
+  }
+  if (nb.dif.true==1 & unique(b$J)==4 & unique(b$M)==4) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1,s[x,"dif_detect_unif_1"]==1  & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
+                                                        ,0)  )
+    flexible.detect <- mean(flexible.detect)
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]),0)  )
+    moreflexible.detect <- mean(moreflexible.detect)
+  }
+  if (nb.dif.true==2 & unique(b$J)==4 & unique(b$M)==4) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
+                                                        ,0)  )
+    flexible.detect <- mean(flexible.detect)
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) &
+                                                              s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0)  )
+    moreflexible.detect <- mean(moreflexible.detect)
+  }
+  if (nb.dif.true==2 & unique(b$J)==7 & unique(b$M)==4) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
+                                                        ,0)  )
+    flexible.detect <- mean(flexible.detect)
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
+                                                              s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0)  )
+    moreflexible.detect <- mean(moreflexible.detect)
+  }
+  if (nb.dif.true==3 & unique(b$J)==7 & unique(b$M)==4) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,"dif_detect_unif_1"]==1 & s[x,"dif_detect_unif_2"]==1 & s[x,"dif_detect_unif_3"]==1 & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) 
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <-  sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) 
+                                                         ,0)  )
+    flexible.detect <- mean(flexible.detect)
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
+                                                              s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) & s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
+    moreflexible.detect <- mean(moreflexible.detect)
+  }
+  if (nb.dif.true==1 & unique(b$J)==4 & unique(b$M)==2) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==1, s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1")])
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <- prop.perfect
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]),0)  )
+    moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:4)]%in%c(s[x,c("real_dif_1")]))/1)
+    percent.detect <- mean(percent.detect)
+  }
+  if (nb.dif.true==2 & unique(b$J)==4 & unique(b$M)==2) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:4),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <- prop.perfect
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:4)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:4)]) &
+                                                              s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:4)]),0)  )
+    moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:4)]%in%c(s[x,c("real_dif_1","real_dif_2")]))/2)
+    percent.detect <- mean(percent.detect)
+    
+  }
+  if (nb.dif.true==2 & unique(b$J)==7 & unique(b$M)==2) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==2,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2")]) 
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <- prop.perfect
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
+                                                              s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]),0)  )
+    moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:7)]%in%c(s[x,c("real_dif_1","real_dif_2")]))/2)
+    percent.detect <- mean(percent.detect)
+  }
+  if (nb.dif.true==3 & unique(b$J)==7 & unique(b$M)==2) {
+    perfect.detection <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))==3,s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[1])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[2])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) & s[x,paste0('dif_detect_',which(sapply(paste0("dif_detect_",1:7),function(y) !is.na(s[x,y])))[3])]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]) 
+                                                          ,0)  )
+    prop.perfect <- mean(perfect.detection)
+    flexible.detect <- prop.perfect
+    moreflexible.detect <- sapply(1:1000,function(x) ifelse(sum(!is.na(s[x,paste0("dif_detect_",1:7)]))!=0,s[x,"real_dif_1"]%in%c(s[x,paste0("dif_detect_",1:7)]) &
+                                                              s[x,"real_dif_2"]%in%c(s[x,paste0("dif_detect_",1:7)]) & s[x,"real_dif_3"]%in%c(s[x,paste0("dif_detect_",1:7)]),0) )
+    moreflexible.detect <- mean(moreflexible.detect)
+    percent.detect <- sapply(1:1000,function(x) sum(s[x,paste0("dif_detect_",1:7)]%in%c(s[x,c("real_dif_1","real_dif_2","real_dif_3")]))/3)
+    percent.detect <- mean(percent.detect)
+  }
   z <- data.frame(m.beta=mean(s$beta),
                   se.empirical.beta=sd(s$beta),
                   se.analytical.beta=mean(s$se_beta),
@@ -693,7 +802,12 @@ compile_simulation2_resali <- function(scenario) {
                   true.value.in.ci.p=mean(true.value.in.ci),
                   h0.rejected.p=mean( (s$beta-1.96*s$se_beta)>0 | (s$beta+1.96*s$se_beta)<0 ),
                   beta.same.sign.truebeta.p=mean(beta.same.sign.truebeta.p),
-                  beta.same.sign.truebeta.signif.p=mean(beta.same.sign.truebeta.p[num.reject])
+                  beta.same.sign.truebeta.signif.p=mean(beta.same.sign.truebeta.p[num.reject]),
+                  dif.detected=dif.d,
+                  prop.perfect=prop.perfect,
+                  flexible.detect=flexible.detect,
+                  moreflexible.detect=moreflexible.detect,
+                  percent.detect=ifelse(name%%2==0,NA,percent.detect)
   )
   d <- cbind(b,a,z)
   d$prop.
diff --git a/RProject/Scripts/functions/resali.R b/RProject/Scripts/functions/resali.R
index 36ba0f3..7fefac8 100644
--- a/RProject/Scripts/functions/resali.R
+++ b/RProject/Scripts/functions/resali.R
@@ -48,8 +48,8 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
     res.uni <- res.anova[[which.max(fval)]][3,"Pr(>F)"]>0.05
     res.uniform <- c(res.uniform,res.uni)
     items_n <- c(items_n[items_n!=paste0('item',res.item)],paste0("item",res.item,c("noTT","TT")))
-    dat[,paste0("item",res.item,'TT')] <- dat[dat$TT==1,paste0('item',res.item)]
-    dat[,paste0("item",res.item,'noTT')] <- dat[dat$TT==0,paste0('item',res.item)]
+    dat[dat$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$TT==0,paste0('item',res.item)]
     resp <- dat[,items_n]
     grp <- dat[,group]
     pcm_while <- TAM::tam.mml(resp=resp,Y=grp,irtmodel = "PCM",est.variance = T,verbose=F)
@@ -118,8 +118,8 @@ resali <- function(df=NULL,items=NULL,group=NULL,verbose=T) {
       res.item <- gsub("[a-z]", "",colnames(resp)[which.max(fval)])
       res.items <- c(res.items,res.item)
       items_n <- c(items_n[items_n!=paste0('item',res.item)],paste0("item",res.item,c("noTT","TT")))
-      dat[,paste0("item",res.item,'TT')] <- dat[dat$TT==1,paste0('item',res.item)]
-      dat[,paste0("item",res.item,'noTT')] <- dat[dat$TT==0,paste0('item',res.item)]
+      dat[dat$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)