diff --git a/Modules/rosali_custom/rosali_original.ado b/Modules/rosali_custom/rosali_original.ado
index a864920..4ac0b30 100644
--- a/Modules/rosali_custom/rosali_original.ado
+++ b/Modules/rosali_custom/rosali_original.ado
@@ -760,6 +760,113 @@ if "`group'"!="" & "`nodif'"=="" { // PARTIE 1 = Slmt si option group & pas de "
   	//Variance et se mA
   	matrix var_mA = (val_mA[1,"/var(THETA)#0bn.`gp'"]\val_mA[2,"/var(THETA)#0bn.`gp'"])
 
+    *************************************************************
+  	***********************AFFICHAGE*****************************
+  	*************************************************************
+
+
+  	//Affichage modèle A
+  	di
+  	di as input "PROCESSING STEP A"
+  	di
+
+  	if "`detail'" != "" {
+  		/* Affichage des estimations des difficultés modèle A */
+
+  		di  _col(5) as text "{ul:MODEL A:} Overall measurement non-invariance between groups"
+  		di
+  		di %~85s as text "Item difficulties: estimates (s.e.)"
+  		di _col(10) "{hline 65}"
+  		di  _col(31) as text abbrev("`gp'",20) "=0" _col(57) abbrev("`gp'",20) "=1"
+  		di _col(10) "{hline 65}"
+  		forvalues j=1/`nbitems' {
+  			di as text _col(10) abbrev("``j''", 18)
+  			forvalues p=1/`nbdif_`j'' {
+  				di as text _col(10) "`p'" as result _col(30) %6.2f `delta`j'_`p'g0mA'  %6.2f " (" %3.2f `delta`j'_`p'g0mA_se' ")"  _col(56) %6.2f `delta`j'_`p'g1mA' " (" %3.2f  `delta`j'_`p'g1mA_se' ")"
+  			}
+  		}
+  		di as text _col(10) "{hline 65}"
+  		/* Affichage des estimations sur le trait latent du modèle A */
+  		di
+  		di %~85s as text "Latent trait distribution"
+  		di _col(10) "{hline 65}"
+  		di _col(31) "Estimate" _col(57) "Standard error"
+  		di _col(10) "{hline 65}"
+  		di _col(10)  "Variance" as result _col(31) %6.2f `=var_mA[1,1]' _col(55) %6.2f `=var_mA[2,1]'
+  		di _col(10) as text "Group effect" as result _col(31) "0 (constrained)"
+  		di _col(10) as text "{hline 65}"
+  		di
+  		di _col(10) as text "No group effect: equality of the latent trait means between groups"
+  		di _col(10) as text "All item difficulties are freely estimated in both groups"
+  		di
+  	}
+  		//*Affichage modèle B
+
+  		di
+  		di as input "PROCESSING STEP B"
+  		di
+
+  			/* Affichage des estimations des difficultés modèle B */
+  	if "`detail'" != "" {
+  		di  _col(5) as text "{ul:MODEL B:} Overall measurement invariance between groups"
+  		di
+  		di %~85s as text "Item difficulties: estimates (s.e.)"
+  		di _col(10) "{hline 65}"
+  		di  _col(31) abbrev("`gp'",20) "=0" _col(57) abbrev("`gp'",20) "=1"
+  		di _col(10) "{hline 65}"
+
+  		forvalues j=1/`nbitems' {
+  			di _col(10) as text "``j''"
+  			forvalues p=1/`nbdif_`j'' {
+  				di as text _col(10) "`p'" as result _col(30) %6.2f `delta`j'_`p'g0mB' " (" %3.2f `delta`j'_`p'g0mB_se' ")"   _col(56) %6.2f `delta`j'_`p'g1mB' " (" %3.2f `delta`j'_`p'g1mB_se' ")"
+  			}
+  		}
+
+  		di _col(10) as text "{hline 65}"
+  			/* Affichage des estimations sur le trait latent du modèle B */
+  		di
+  		di %~85s as text "Latent trait distribution"
+  		di _col(10) "{hline 65}"
+  		di _col(28) "Estimate" _col(42) "Standard error" _col(62) "P-value"
+  		di _col(10) "{hline 65}"
+  		di _col(10)  "Variance" as result _col(28) %6.2f `=var_mB[1,1]' _col(40) %6.2f `=var_mB[2,1]'
+  		di _col(10) as text "Group effect" as result _col(28) %6.2f `geffmB' _col(40) %6.2f `segeffmB' _col(62) %6.4f `gcmBp'
+  		di _col(10) as text "{hline 65}"
+  		di
+  		di _col(10) as text "Group effect estimated: mean of the latent trait of group 1 freely estimated"
+  		di _col(10) "Equality of the item difficulties between groups"
+  		di
+  	}
+
+  		*****************************************************
+  		*			Modèle A vs Modèle B 					*
+  		*****************************************************
+
+  		qui lrtest modeldifA modeldifB
+  		local diftestp=r(p)
+  		local diftestchi=r(chi2)
+  		local diftestdf=r(df)
+  		//affichage lrtest
+  		di as input "LIKELIHOOD-RATIO TEST"
+  		di
+  		di %~60s "Model A vs Model B"
+  		di _col(10) "{hline 40}"
+  		di _col(10) as text "Chi-square" _col(28) "DF" _col(40) "P-value"
+  		di _col(10) as result %6.2f `diftestchi' _col(28) %2.0f `diftestdf' _col(40) %6.4f `diftestp'
+  		di _col(10) as text "{hline 40}"
+  		di
+
+
+  	if `diftestp'<0.05{
+  		di as result "DIFFERENCE IN ITEM DIFFICULTIES BETWEEN GROUPS LIKELY"
+  	}
+  	else{
+  		di as result "NO DIFFERENCE BETWEEN GROUPS DETECTED"
+  	}
+
+
+
+
 	*********************************
 	*************MODEL C*************
 	*********************************
@@ -787,15 +894,12 @@ if "`group'"!="" & "`nodif'"=="" { // PARTIE 1 = Slmt si option group & pas de "
 			local nbsig=0
 			local minpval=1
 			local itemdif=0
-			if "`detail'" != ""{
-
 				di as text "Loop `boucle'"
 				di as text _col(5) "Adjusted  alpha: " %6.4f  `pajust'
 				di
 				di as text _col(10) "{hline 65}"
 				di as text _col(10) "Freed item" _col(31) "Chi-Square"  _col(48) "DF" _col(57) "P-Value"
 				di as text _col(10) "{hline 65}"
-			}
 			/*boucle de test*/
 			forvalues j=1/`nbitems'{
 				//if `nbdif_`j'' > 2 {
@@ -856,40 +960,32 @@ if "`group'"!="" & "`nodif'"=="" { // PARTIE 1 = Slmt si option group & pas de "
 								local itemdif=`j'
 							}
 						}
-						if "`detail'" != "" {
 							di as text  _col(10) abbrev("``j''",15)  as result _col(31) %6.3f test_dif_`boucle'[`j',1] _col(48) test_dif_`boucle'[`j',2] _col(57)  %6.4f test_dif_`boucle'[`j',3]
-						}
+
 					}
 			}
 			/*si nb de tests significatifs=0, on arrête*/
 			if `nbsig'==0{
 				local stop=1
 				if `boucle' == 1 {
-					if "`detail'" != "" {
 						di as text _col(10) "{hline 65}"
 						di
 						di as result  "No significant test: no difference between groups detected, no DIF detected"
 						di
-					}
 				}
 				else {
-					if "`detail'" != ""{
 						di as text _col(10) "{hline 65}"
 						di
 						di as result "No other significant tests"
 						di
-					}
 				}
 			}
 			else{/*si nb de tests significatifs>0, mise à jour de la matrice de résultats*/
 				matrix dif_rc[`itemdif',1]=`boucle'
-				if "`detail'" != ""{
 					di as text _col(10) "{hline 65}"
 					di
 					di as result "Difference between groups on ``itemdif'' at time 1"
-				}
 				if `nbmoda_`itemdif'' > 2 {
-					if "`detail'" != "" {
 
 						di
 						di %~60s as text "Test of uniform difference"
@@ -897,7 +993,7 @@ if "`group'"!="" & "`nodif'"=="" { // PARTIE 1 = Slmt si option group & pas de "
 						di _col(10) as text "Chi-square" _col(28) "DF" _col(40) "P-value"
 						di _col(10) as result %4.2f `=test_difu_`boucle'[`itemdif',1]' _col(28) `=test_difu_`boucle'[`itemdif',2]' _col(40) %4.2f `=test_difu_`boucle'[`itemdif',3]'
 						di _col(10) as text "{hline 40}"
-					}
+					
 					if test_difu_`boucle'[`itemdif',3]<0.05{	/*DIF NU détectée*/
 						matrix dif_rc[`itemdif',2]=0
 							di
diff --git a/Scripts/Analysis/DIF-ROSALI/pcm_dif_rosali.do b/Scripts/Analysis/DIF-ROSALI/pcm_dif_rosali.do
index 3e52f18..e40cc48 100644
--- a/Scripts/Analysis/DIF-ROSALI/pcm_dif_rosali.do
+++ b/Scripts/Analysis/DIF-ROSALI/pcm_dif_rosali.do
@@ -8,11 +8,11 @@
 *
 *
 *================================================================================================================================================
-adopath+"/home/corentin/Documents/These/Recherche/ROSALI-SIM/Modules/rosali_custom"
+adopath+"/home/corentin/Documents/These/Recherche/Simulations/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"
+ local ss = "1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20"
  foreach s in `ss' {
  foreach Nnn in `N' {
  local Nn =  `Nnn'
@@ -21,6 +21,7 @@ local N = "50 100 200 300"
    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 path_log = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/ROSALI-DIF/log/"
  local scenarios = "A B C D E F G"
  if (`s' <= 4) {
    local scenarios = "A B C D E"
@@ -29,7 +30,7 @@ local N = "50 100 200 300"
  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
   }
@@ -63,9 +64,9 @@ local N = "50 100 200 300"
     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 taillemat=2*`nbitems'*`nbmoda'+`nbitems'+`nbdif'+2+1
   if (mod(`s',2)==0) {
-    local taillemat=2*`nbitems'*`nbmoda'+`nbitems'+`nbitems'+`nbdif'+2
+    local taillemat=2*`nbitems'*`nbmoda'+`nbitems'+`nbitems'+`nbdif'+2+1
   }
   local colna=""
   forvalues i=1/`nbitems' {
@@ -86,16 +87,20 @@ local N = "50 100 200 300"
   forvalues i=1/`nbdif' {
     local colna = "`colna'"+"real_dif_`i' "
   }
- local colna = "`colna'" + "beta " + "se_beta"
-
+ 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 {
-    if (mod(`k',100)==0) {
-      di "`k'/1000"
-    }
+  forvalues k=1/10 {
+    di "###################################################################################"
+    di "###################################################################################"
+    di "###################################################################################"
+    di "Scenario `s'`scen' N=`Nn' ########## `k'/1000"
+    di "###################################################################################"
+    di "###################################################################################"
+    di "###################################################################################"
+
     preserve
     qui keep if replication==`k'
 
@@ -253,10 +258,10 @@ local N = "50 100 200 300"
 
 
     * ROSALI
-    qui rosali_original item1-item`nbitems' item1-item`nbitems', group(tt)
+    rosali_original 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
@@ -329,7 +334,7 @@ local N = "50 100 200 300"
       local mod = "`mod'" + "(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent"
     }
     *calcul du modèle
-    qui `mod'
+    `mod'
     mat V=r(table)
     mat W=V[1..2,1...]
 
@@ -372,8 +377,10 @@ local N = "50 100 200 300"
     }
     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
  }