Added scenario 6 DIF analysis

RProject/pcm.R

@@ -130,7 +130,7 @@ replicate_pcm_analysis<- function(df=NULL,treatment='TT',irtmodel='PCM2',method=
   j <- max(df$item1)
   if(j==1) {
     return(replicate_pcm_analysis_m2(df=NULL,treatment='TT',irtmodel='PCM2',method='MML',sequence='replication',truebeta=0,eff.size=0,difsize=NA,nbdif=0))
-  } else if (j==3) {
+  } else {
     return(replicate_pcm_analysis_m4(df=NULL,treatment='TT',irtmodel='PCM2',method='MML',sequence='replication',truebeta=0,eff.size=0,difsize=NA,nbdif=0))
   }
 }

Scripts/Analysis/NoDIF/pcm_dif_100.do

@@ -0,0 +1,148 @@
+  *=================================================================================================================================================
+  * 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)
+  *
+  * outputs :  for N=100
+  *
+  *
+  *================================================================================================================================================
+
+  * Load pcm.ado
+  adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
+
+  *==========================
+  * Scenarios with : J=4
+  *==========================
+
+  ** 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'/out/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
+  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)(2.item`i'<-THETA@2)"
+    }
+  }
+  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',3*`j'-2] = W[1,6*`j'-3] // items avant le premier dif
+      mat outmat[`k',3*`j'-1] = W[1,6*`j'-1] // items avant le premier dif
+      mat outmat[`k',3*`j'] =   W[1,6*`j'] // items avant le premier dif
+      }
+  else if (`j'==`difitems1') {
+      mat outmat[`k',3*`j'-2] = W[1,6*`j'-2] // items du le premier dif
+      mat outmat[`k',3*`j'-1] = W[1,6*`j'+1] // items du le premier dif
+      mat outmat[`k',3*`j'] =   W[1,6*`j'+4] // items du le premier dif    }
+    }
+  else {
+      mat outmat[`k',3*`j'-2] = W[1,6*`j'+1] // items apres le premier dif
+      mat outmat[`k',3*`j'-1] = W[1,6*`j'+3] // items apres le premier dif
+      mat outmat[`k',3*`j'] =   W[1,6*`j'+4] // items apres le premier dif    }
+    }
+  }
+    mat outmat[`k',3*`nbitems'+1] = W[1,6*`difitems1'-4] // coef de dif
+    mat outmat[`k',3*`nbitems'+2] = W[1,6*`difitems1'-1] // coef de dif
+    mat outmat[`k',3*`nbitems'+3] = W[1,6*`difitems1'+2] // coef de dif
+    mat outmat[`k',3*`nbitems'+4] = W[1,6*`nbitems'+5] // beta
+    mat outmat[`k',3*`nbitems'+5] = W[2,6*`nbitems'+5] // se beta
+    mat outmat[`k',3*`nbitems'+6] = `difitems1' // numéro item de dif
+    restore
+}
+putexcel set "`path_res'/out/6`scen'_`Nn'.xls", sheet("outmat") replace
+putexcel A1=matrix(outmat), colnames
+}
+}

Scripts/Analysis/NoDIF/pcm_nodif_100.do

@@ -1,77 +0,0 @@
-  *=================================================================================================================================================
-  * 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)
-  *
-  * outputs :  for N=100
-  *
-  *
-  *================================================================================================================================================
-
-  * Load pcm.ado
-  adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
-
-  *==========================
-  * Scenarios with : J=4
-  *==========================
-
-  ** 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"
-  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'/out/5`scen'_`Nn'.xls", sheet("outmat") replace
-  putexcel A1=matrix(outmat), colnames
-}
-}