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1503 lines
43 KiB
Plaintext
1503 lines
43 KiB
Plaintext
7 months ago
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/********************************************************************************/
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/* v1.1 : Modified for being used after irt pcm and irt rsm */
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/********************************************************************************/
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* Needed modules :
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* gausshermite (http://www.freeirt.org)
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* gllamm version 2.3.14 (ssc describe gllamm)
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program define pcmtest, rclass
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version 11.0
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syntax [, APproximation NEw Group(string) NFit(string) Power(string) Alpha(string) GRAPHics FILEgraph(string) Sitest]
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preserve
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qui{
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tempfile bddtravail
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save `bddtravail', replace
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tempname x w val freq
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capture local cmdavant=e(cmd)
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if _rc!=0 | "`cmdavant'"!="pcmodel"{
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capture local cmdavant=e(model1)
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local condition ="`cmdavant'"=="pcm" | "`cmdavant'"=="rsm"
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if _rc!=0 | `condition'!=1{
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noi di in red "Please use pcmtest only after pcmodel, irt pcm or irt rsm"
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error 100
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}
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else{
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local testIrtPcm=1
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}
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if "`cmdavant'"=="rsm"{
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local RSMtest=1
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}
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}
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if "`graphics'"!=""{
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if "`filegraph'"!=""{
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local ReplaceGr2=0
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local ReplaceGr=strpos("`filegraph'",",")
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if `ReplaceGr'!=0{
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local ReplaceGr=strpos(reverse("`filegraph'"),",")
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local ReplaceGr2=strpos( substr("`filegraph'", strpos("`filegraph'",","), .), "r")!=0
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local filegraphOld="`filegraph'"
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local filegraph=rtrim(reverse(substr(reverse("`filegraph'"),`=`ReplaceGr'+1',.)))
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}
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if `ReplaceGr2'==0{
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capture graph use "`filegraph'_LT_Sc", nodraw
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if _rc==0{
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noi di in red "`filegraph'_LT_Sc already exists (use option replace for replacing it)"
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error 100
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}
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capture graph use "`filegraph'_MAP", nodraw
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if _rc==0{
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noi di in red "`filegraph'_MAP already exists (use option replace for replacing it)"
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error 100
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}
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capture graph use "`filegraph'_Score_Distrib", nodraw
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if _rc==0{
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noi di in red "`filegraph'_Score_Distrib already exists (use option replace for replacing it)"
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error 100
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}
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capture graph use "`filegraph'_Contrib", nodraw
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if _rc==0{
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noi di in red "`filegraph'_Contrib already exists (use option replace for replacing it)"
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error 100
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}
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}
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capture save "`filegraph'", replace
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if _rc!=0{
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noi di in red "Invalid path specification"
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error 603
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}
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else{
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erase "`filegraph'.dta"
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}
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}
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}
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/***************************/
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/* Récuperation de toutes */
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/* les matrices estimées */
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/***************************/
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local itest=e(itest)
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if `itest'==0{
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noi di in red "No tests of fit if the items difficulties are fixed (i.e. not estimated) "
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error 100
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}
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local Elll=e(ll)
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local Ecn=e(cn)
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local EN=e(N)
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local ENit=e(Nit)
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local dataR1m=e(dataR1m)
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local mugauss=e(mugauss)
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local sdgauss=e(sdgauss)
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local ordre=e(order)
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local ENqual=e(Ncat)
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local ENquant=e(Ncont)
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local convergeance=e(converged)
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local Esigma=e(sigma)
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local EVarsigma=e(Varsigma)
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local ENumFit=e(NumFit)
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local Eitems=e(items)
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local IF=e(if)
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local IN=e(in)
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if "`IF'"!="" & "`IF'"!="."{
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local if "`IF'"
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}
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if "`IN'"!="" & "`IN'"!="."{
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local in "`IN'"
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}
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tempname EglobalFit EitemFit Etheta EVartheta Edelta EVardelta
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matrix `EglobalFit'=e(globalFit)
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matrix `EitemFit'=e(itemFit)
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matrix `Etheta'=e(theta)
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matrix `EVartheta'=e(Vartheta)
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matrix `Edelta'=e(delta)
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matrix `EVardelta'=e(Vardelta)
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local rsm=e(rsm)
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if "`rsm'"!="."{
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local RSMtest2=1
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}
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else if "`RSMtest'"=="1"{
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local RSMtest2=1
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}
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else{
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local RSMtest2=0
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}
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/* irt pcm et irt rsm */
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if "`testIrtPcm'"=="1"{
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local EN=e(N)
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local mugauss=0
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local if strpos(,s2)
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local IFif=e(cmdline)
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local PosIf=strpos("`IFif'"," if ")
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local PosIn=strpos("`IFif'"," in ")
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if strpos("`IFif'",",")==0{
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local posComma="."
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}
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else{
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local posComma=strpos("`IFif'",",")
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}
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if `PosIf'!=0 & `PosIn'!=0{
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if `PosIf'<`PosIn'{
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local if "`=substr("`IFif'",`=`PosIf'+4',`=`PosIn'-`PosIf'-4')'"
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local in "`=substr("`IFif'",`=`PosIn'+4',`=`posComma'-`PosIn'-4')'"
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}
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else{
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local in "`=substr("`IFif'",`=`PosIn'+4',`=`PosIf'-`PosIn'-4')'"
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local if "`=substr("`IFif'",`=`PosIf'+4',`=`posComma'-`PosIf'-4')'"
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}
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}
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else{
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local if "`=substr("`IFif'",`=`PosIf'+4',`=`posComma'-`PosIf'-4')'"
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local in "`=substr("`IFif'",`=`PosIn'+4',`=`posComma'-`PosIn'-4')'"
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}
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if `PosIf'==0{
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local if=""
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}
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if `PosIn'==0{
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local in=""
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}
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local itPcm=e(n_cuts1)
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tempname Edelta DifComPcm tempmatdif EglobalFit EitemFit Etheta EVartheta EVardelta
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matrix `DifComPcm'=e(b)
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local nbcolMD=0
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local plus=0
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matrix `Edelta'=(.)
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foreach i in `itPcm'{
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local sum=0
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forvalues it=2/`i'{
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local tempmatdifnnn=`DifComPcm'[1,`=2*`it'+`plus'']-`DifComPcm'[1,`=2*`=`it'-1'+`plus'']
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matrix `tempmatdif'=(`=-`tempmatdifnnn'')
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matrix `Edelta'=`Edelta',`tempmatdif'
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}
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local plus=`plus'+2*`i'
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}
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matrix `Edelta'=`Edelta'[....,2...]
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local sdgauss=`DifComPcm'[1,3]
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local Eitems=e(items1)
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}
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qui capture matrix list r(globalFitTot)
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if _rc!=0{
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local testafaire=1
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}
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else{
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local testafaire=0
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}
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if "`new'"!=""{
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local testafaire=1
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}
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if "`nfit'"!=""{
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local numFit=`nfit'
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}
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else{
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local numFit=.
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}
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local varlist `Eitems'
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local nbit: word count `varlist'
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local nbitsuf=1
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if `nbit'<2{
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noi di in red "No tests of fit if the number of items is less than 2"
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error 100
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}
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if `nbit'==2{
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noi di in gr "Only the R1m test is performed if the number of items is equal to 2"
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local nbitsuf=0
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}
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tokenize `varlist'
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qui{
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marksample touse,novarlist
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keep if `touse'
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local ordre=0
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forvalues i=1/`nbit'{
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tempname rep__`i'
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tab ``i'', matrow(`rep__`i'')
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local ordre=`ordre'+`=rowsof(`rep__`i'')'-1
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forvalues j=1/`=rowsof(`rep__`i'')'{
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replace ``i''=`j'-1 if ``i''==`rep__`i''[`j',1]
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}
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}
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if `RSMtest2'==1{
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local ordre=`=rowsof(`rep__1')'-2+`nbit'
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}
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q memory
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}
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tempfile bddini datatest bdd_b bdd_se bdd_seg bdd_P bdd_R1 bdd_G
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save `bdd_b', replace
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save `datatest', replace
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/*************************************/
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/* test R1m */
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/*************************************/
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noi di in gr "Performing R1m test"
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qui{
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q memory
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local matsizeini=r(matsize)
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set matsize `matsizeini'
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tempfile matU matU1 matU2
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tempname dm cell row
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egen `dm'=rowmiss(`varlist')
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replace `dm'=`dm'>0
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tab `dm',matcell(`cell') matrow(`row')
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local nbmissing=`cell'[2,1]
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local percentmissing=`cell'[2,1]/(`cell'[1,1]+`cell'[2,1])
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if `nbmissing'==.{
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local nbmissing=0
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local percentmissing=0
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}
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keep if `dm'==0
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local NbIdFit=_N
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if `numFit'==.{
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local propFit=1
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local propFitPb=0
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}
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else if `numFit'>`NbIdFit'{
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local propFit=1
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local propFitPb=1
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}
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else{
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local propFit=`numFit'/`NbIdFit'
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local propFitPb=2
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}
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drop `dm'
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keep `varlist'
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forvalues i=1/`nbit'{
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rename ``i'' pre_``i''
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}
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forvalues i=1/`nbit'{
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gen it`i'=pre_``i''
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drop pre_``i''
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}
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local nbscore=1
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forvalues i=1/`nbit'{
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qui tab it`i'
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local nbmoda_`i'=r(r)
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local nbscore=`nbscore'+`nbmoda_`i''-1
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}
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local score "it1"
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forvalues i=2/`nbit'{
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local score "`score'+it`i'"
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}
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gen score=`score'
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save `bdd_se', replace
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local N=_N
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/* autogroup */
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if "`group'"==""{
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su score, d
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local list `=r(p25)'
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if `=r(p25)'!=`=r(p50)'{
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local list "`list' `=r(p50)'"
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}
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if `=r(p50)'!=`=r(p75)'{
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local list "`list' `=r(p75)'"
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}
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if `=r(p75)'!=`=`nbscore'-1'{
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local list "`list' `=`nbscore'-1'"
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}
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if wordcount("`list'")==1{
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noi di in red "Problem with Autogroup option: creating groups from the score quartiles is not possible"
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}
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tab score, matcell(`freq') matrow(`val')
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local nbgroup=wordcount("`list'")
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}
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else{
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tab score, matcell(`freq') matrow(`val')
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local list "`group'"
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local nbgroup=wordcount("`list'")
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if real(word("`list'",`nbgroup'))<`=`nbscore'-1'{
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local list "`group' `=`nbscore'-1'"
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local nbgroup=wordcount("`list'")
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}
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||
|
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}
|
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local nbmodagpe=0
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forvalues i=1/`nbit'{
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local nbmodagpe=`nbmodagpe'+`nbmoda_`i''
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}
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|
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gen g=.
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local liminf1=-1
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forvalues i=1/`nbgroup'{
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local limsup`i'=real("`=word("`list'",`i')'")
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|
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if `i'>1{
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local liminf`i'=real("`=word("`list'",`=`i'-1')'")
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|
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}
|
||
|
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replace g=`i' if score<=`limsup`i'' & score>`liminf`i''
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}
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|
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forvalues i=1/`nbgroup'{
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su score if g==`i'
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local N`i'=r(N)
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|
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}
|
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|
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save `bdd_se', replace
|
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|
|
save `bdd_seg', replace
|
||
|
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use `bdd_se', replace
|
||
|
|
local count=0
|
||
|
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forvalues i=1/`nbit'{
|
||
|
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forvalues j=1/`nbmoda_`i''{
|
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|
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if `j'==1{
|
||
|
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local diffest`i'_`j'=0
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|
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}
|
||
|
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else{
|
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|
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local count=`count'+1
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|
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local diffest`i'_`j'=round(`Edelta'[1,`count'],0.001)+`diffest`i'_`=`j'-1''
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||
|
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}
|
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|
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local num`i'_`j' "exp(`=`j'-1'*x-`diffest`i'_`j'')"
|
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|
|
if `j'==1{
|
||
|
|
local denom`i' "1"
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local denom`i' "`denom`i''+`num`i'_`j''"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
local PCM`i'_`j' "(`num`i'_`j'')/(`denom`i'')"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local nbcomb=1
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
local nbcomb=`nbcomb'*`nbmoda_`i''
|
||
|
|
}
|
||
|
|
clear
|
||
|
|
set obs `=int(`nbcomb'+0.1)'
|
||
|
|
local facteur=1
|
||
|
|
gen score=0
|
||
|
|
local order "score"
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
gen it`i'=floor(mod(_n/`facteur',`nbmoda_`i''))
|
||
|
|
local facteur=`facteur'*`nbmoda_`i''
|
||
|
|
replace score=score+it`i'
|
||
|
|
tab it`i', gen(i`i'c)
|
||
|
|
local order "`order' it`i'"
|
||
|
|
}
|
||
|
|
order `order', first
|
||
|
|
sort score
|
||
|
|
tab score, gen(score)
|
||
|
|
local nbscore=r(r)
|
||
|
|
gen P=1
|
||
|
|
local gdN=_N
|
||
|
|
|
||
|
|
/*************************************/
|
||
|
|
/* */
|
||
|
|
/* Calcul de la probabilité de */
|
||
|
|
/* chaque patern de réponses */
|
||
|
|
/* */
|
||
|
|
/*************************************/
|
||
|
|
|
||
|
|
if "`approximation'"==""{
|
||
|
|
local percentcount=0
|
||
|
|
noi di ""
|
||
|
|
noi di in ye "`gdN'" in gr " response pattern probabilities to compute"
|
||
|
|
noi di in gr "Percentage of completion"
|
||
|
|
noi di in gr "----|---10%---|---20%---|---30%---|---40%---|---50%"
|
||
|
|
_dots 0, title(Loop computation of theorical probabilities of each response pattern) reps(100)
|
||
|
|
forvalues l=1/`gdN'{
|
||
|
|
local exp ""
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
forvalues m=1/`nbmoda_`i''{
|
||
|
|
if i`i'c`m'[`l']==1{
|
||
|
|
if "`exp'"==""{
|
||
|
|
local exp "`PCM`i'_`m''"
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local exp "`exp'*`PCM`i'_`m''"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
gausshermite `exp' , sigma(`sdgauss') mu(`mugauss') display
|
||
|
|
replace P=round(r(int),0.000001) if _n==`l'
|
||
|
|
local percentcountplus=floor(`l'*100/`gdN')
|
||
|
|
forvalues percen=`=`percentcount'+1'/`percentcountplus'{
|
||
|
|
nois _dots `percen' 0
|
||
|
|
}
|
||
|
|
local percentcount=`percentcountplus'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
noi di in gr "Response pattern probabilities computation"
|
||
|
|
replace P=0
|
||
|
|
sort score it*
|
||
|
|
save `bdd_P', replace
|
||
|
|
local NbCol=1
|
||
|
|
local compteur=1
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
tempname Dit`i'
|
||
|
|
matrix `Dit`i''=`Edelta'[1,`compteur'..`=`compteur'+`nbmoda_`i''-2']
|
||
|
|
if colsof(`Dit`i'')>`NbCol'{
|
||
|
|
local NbCol=colsof(`Dit`i'')
|
||
|
|
}
|
||
|
|
local compteur=`compteur'+`nbmoda_`i''-1
|
||
|
|
}
|
||
|
|
clear
|
||
|
|
noi di in gr "----|---25%---|---50%---|---75%---|---100%
|
||
|
|
qui _dots 0, title(Title) reps(40)
|
||
|
|
set obs 1000000
|
||
|
|
gen id=_n
|
||
|
|
gen theta=`mugauss'+invnormal(uniform())*`sdgauss'
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
gen denom`i'=1
|
||
|
|
gen num`i'_0=1
|
||
|
|
forvalues j=1/`=`nbmoda_`i''-1'{
|
||
|
|
gen num`i'_`j'=exp(ln(num`i'_`=`j'-1') + theta-`Dit`i''[1,`j'])
|
||
|
|
replace denom`i'=denom`i'+num`i'_`j'
|
||
|
|
}
|
||
|
|
forvalues j=0/`=`nbmoda_`i''-1'{
|
||
|
|
gen p`i'_`j'=num`i'_`j'/denom`i'
|
||
|
|
}
|
||
|
|
drop denom`i'
|
||
|
|
drop num`i'_*
|
||
|
|
forvalues j=1/`=`nbmoda_`i''-1'{
|
||
|
|
replace p`i'_`j'=p`i'_`j'+p`i'_`=`j'-1'
|
||
|
|
}
|
||
|
|
gen it`i'=0
|
||
|
|
gen random`i'=runiform()
|
||
|
|
forvalues j=1/`=`nbmoda_`i''-1'{
|
||
|
|
replace it`i'=`j' if random`i'>=p`i'_`=`j'-1' & random`i'<p`i'_`j'
|
||
|
|
}
|
||
|
|
drop random* p`i'_*
|
||
|
|
forvalues j=1/`=round(`=40/`nbit'')'{
|
||
|
|
nois _dots `j' 0
|
||
|
|
}
|
||
|
|
}
|
||
|
|
egen score=rowtotal(it*)
|
||
|
|
keep it* score
|
||
|
|
contract score it*, f(P)
|
||
|
|
replace P=round(P/1000000,0.000001)
|
||
|
|
sort score it*
|
||
|
|
merge score it* using `bdd_P'
|
||
|
|
drop _merge
|
||
|
|
order `order', first
|
||
|
|
order P, last
|
||
|
|
}
|
||
|
|
noi di in gr ""
|
||
|
|
save `bdd_R1', replace
|
||
|
|
local dataR1m "`bdd_R1'"
|
||
|
|
tab score
|
||
|
|
local Pscoresl=r(r)
|
||
|
|
tempname Pscores
|
||
|
|
matrix `Pscores'=J(`Pscoresl',2,.)
|
||
|
|
forvalues i=1/`Pscoresl'{
|
||
|
|
su P if score==`=`i'-1'
|
||
|
|
matrix `Pscores'[`i',2]=r(sum)
|
||
|
|
matrix `Pscores'[`i',1]=`i'-1
|
||
|
|
}
|
||
|
|
save `matU2', replace
|
||
|
|
local sort "score"
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
local sort "`sort' it`i'"
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
replace i`i'c`j'=i`i'c`j'*P
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues i=1/`nbscore'{
|
||
|
|
replace score`i'=score`i'*P
|
||
|
|
}
|
||
|
|
save `matU1', replace
|
||
|
|
/* Matrices U */
|
||
|
|
noi di "U matrix computation"
|
||
|
|
local order ""
|
||
|
|
forvalues i=1/`=wordcount("`list'")'{
|
||
|
|
tempfile b`i'_1
|
||
|
|
local nbscoreg`i'= `nbscore'
|
||
|
|
forvalues j=0/`=`nbscore'-1'{
|
||
|
|
if `j'>`limsup`i'' | `j'<=`liminf`i''{
|
||
|
|
local nbscoreg`i'=`nbscoreg`i''-1
|
||
|
|
capture drop s`=`j'+1'g`i'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local order "`order' *g`i'"
|
||
|
|
use `matU1', replace
|
||
|
|
keep if score<=`limsup`i'' & score>`liminf`i''
|
||
|
|
gen g=`i'
|
||
|
|
forvalues a=1/`nbit'{
|
||
|
|
forvalues b=1/`nbmoda_`a''{
|
||
|
|
capture rename i`a'c`b' i`a'c`b'g`i'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues a=1/`nbscore'{
|
||
|
|
capture rename score`a' s`a'g`i'
|
||
|
|
forvalues j=1/`=wordcount("`list'")'{
|
||
|
|
if `=`a'-1'>`limsup`i'' | `=`a'-1' <= `liminf`i''{
|
||
|
|
capture drop s`a'g`j'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
tempfile bloc`i'
|
||
|
|
sort `sort'
|
||
|
|
save `b`i'_1', replace
|
||
|
|
}
|
||
|
|
local order ""
|
||
|
|
forvalues i=1/`=wordcount("`list'")'{
|
||
|
|
tempfile b`i'_2
|
||
|
|
local order "`order' *g`i'"
|
||
|
|
use `matU2', replace
|
||
|
|
keep if score<=`limsup`i'' & score>`liminf`i''
|
||
|
|
gen g=`i'
|
||
|
|
forvalues a=1/`nbit'{
|
||
|
|
forvalues b=1/`nbmoda_`a''{
|
||
|
|
capture rename i`a'c`b' i`a'c`b'g`i'b
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues a=1/`nbscore'{
|
||
|
|
capture rename score`a' s`a'g`i'b
|
||
|
|
forvalues j=1/`=wordcount("`list'")'{
|
||
|
|
|
||
|
|
if `=`a'-1'>`limsup`i'' | `=`a'-1' <= `liminf`i''{
|
||
|
|
capture drop s`a'g`j'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
sort `sort'
|
||
|
|
save `b`i'_2', replace
|
||
|
|
describe
|
||
|
|
local mat_`i'=r(k)-3-`nbit'
|
||
|
|
}
|
||
|
|
noi di "W matrix computation"
|
||
|
|
/* Matrice W */
|
||
|
|
local nbscoreg0=0
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
tempname W_`g'i W_`g'
|
||
|
|
tempfile b`g'_2b
|
||
|
|
qui q memory
|
||
|
|
if `mat_`g''>r(matsize) & `mat_`g''<=r(m_matsize){
|
||
|
|
set matsize `mat_`g''
|
||
|
|
}
|
||
|
|
if `mat_`g''>r(m_matsize){
|
||
|
|
noi di in red "Error, not enough memory to allocate to the W matrix computation"
|
||
|
|
}
|
||
|
|
matrix `W_`g''=J(`mat_`g'',`mat_`g'',.)
|
||
|
|
use `b`g'_2', replace
|
||
|
|
local count=1
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
rename i`i'c`j'g`g'b v`count'b
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues s=1/`=`nbscore'+1'{
|
||
|
|
capture rename s`s'g`g'b v`count'b
|
||
|
|
if _rc ==0{
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local Ncol_`g'_=`count'-1
|
||
|
|
save `b`g'_2b', replace
|
||
|
|
use `b`g'_1', replace
|
||
|
|
local count=1
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
rename i`i'c`j'g`g' v`count'
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues s=1/`=`nbscore'+1'{
|
||
|
|
capture rename s`s'g`g' v`count'
|
||
|
|
if _rc ==0{
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local Ncol_`g'__=`count'-1
|
||
|
|
forvalues i=1/`=`count'-1'{
|
||
|
|
replace v`i'=P if round(v`i',0.000001)!=round(0,0.000001)
|
||
|
|
}
|
||
|
|
local countW_`g'=`count'-1
|
||
|
|
merge `sort' using `b`g'_2b'
|
||
|
|
drop _merge
|
||
|
|
forvalues i=1/`mat_`g''{
|
||
|
|
forvalues j=1/`mat_`g''{
|
||
|
|
gen prod=v`i'*v`j'b
|
||
|
|
qui su prod
|
||
|
|
matrix `W_`g''[`i',`j']=r(sum)
|
||
|
|
drop prod
|
||
|
|
}
|
||
|
|
}
|
||
|
|
capture matrix `W_`g'i'=invsym(`W_`g'')
|
||
|
|
if _rc!=0{
|
||
|
|
capture matrix `W_`g'i'=inv(`W_`g'')
|
||
|
|
}
|
||
|
|
if _rc!=0{
|
||
|
|
noi di in red "Error while computing the Wg matrix"
|
||
|
|
}
|
||
|
|
tempname A rank_
|
||
|
|
mata: `A'=J(1,1,.)
|
||
|
|
mata: `A'[1,1]=rank(st_matrix("`W_`g''"))
|
||
|
|
mata: st_matrix("`rank_'",`A')
|
||
|
|
local rank`g'=`rank_'[1,1]
|
||
|
|
}
|
||
|
|
/* Matrice poid */
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
tempfile bddSe`g' b`g'_2bi
|
||
|
|
use `bdd_seg', replace
|
||
|
|
keep if g==`g'
|
||
|
|
gen Pd=1
|
||
|
|
contract `sort', f(nb)
|
||
|
|
sort `sort'
|
||
|
|
save `bddSe`g'', replace
|
||
|
|
use `b`g'_2b', replace
|
||
|
|
sort `sort'
|
||
|
|
merge `sort' using `bddSe`g''
|
||
|
|
drop _merge
|
||
|
|
replace nb=0 if nb==.
|
||
|
|
gen nbth=P*`N'
|
||
|
|
gen Di=(nb-nbth)/sqrt(`N')
|
||
|
|
sort `sort'
|
||
|
|
save `b`g'_2bi', replace
|
||
|
|
if `countW_`g''>10{
|
||
|
|
set matsize `countW_`g''
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
set matsize 10
|
||
|
|
}
|
||
|
|
tempname deviation_`g'
|
||
|
|
matrix `deviation_`g''=J(`countW_`g'',1,.)
|
||
|
|
use `b`g'_2bi', replace
|
||
|
|
gen Pobs=nb/`N'
|
||
|
|
gen Diff=Pobs-P
|
||
|
|
forvalues j=1/`countW_`g''{
|
||
|
|
replace v`j'b=v`j'b*Diff
|
||
|
|
su v`j'b
|
||
|
|
matrix `deviation_`g''[`j', 1]=r(sum)*sqrt(`N')
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local sum=0
|
||
|
|
local ddl=0
|
||
|
|
local rank ""
|
||
|
|
qui q memory
|
||
|
|
if `matsizeini'>r(matsize) & 10000 > r(m_matsize){
|
||
|
|
set matsize `matsizeini'
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
set matsize 10000
|
||
|
|
}
|
||
|
|
tempname graphContribPond
|
||
|
|
matrix `graphContribPond'=J(`nbgroup',2,.)
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
tempname G_`g'
|
||
|
|
capture matrix `G_`g''=`deviation_`g'''*`W_`g'i'*`deviation_`g''
|
||
|
|
if _rc!=0{
|
||
|
|
noi di in red "Error, not enought memory to allocate to the W matrix computation
|
||
|
|
}
|
||
|
|
local sum=`sum'+`G_`g''[1,1]
|
||
|
|
local ddl=`ddl'+`rank`g''
|
||
|
|
local rank "`rank'`rank`g'' "
|
||
|
|
matrix `graphContribPond'[`g',1]=`g'
|
||
|
|
matrix `graphContribPond'[`g',2]=`G_`g''[1,1]
|
||
|
|
}
|
||
|
|
local ddl=`ddl'-`ordre'-1
|
||
|
|
set matsize `matsizeini'
|
||
|
|
}
|
||
|
|
local R1m_group "`list'"
|
||
|
|
local R1m_Rank `rank'
|
||
|
|
local R1M_ddl=`ddl'
|
||
|
|
local R1M_stat=`sum'*`propFit'
|
||
|
|
local R1M_p=`=1-chi2(`ddl', `R1M_stat')'
|
||
|
|
|
||
|
|
/*************************************/
|
||
|
|
/* tests Si */
|
||
|
|
/*************************************/
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
qui{
|
||
|
|
local countbase=0
|
||
|
|
forvalues ii=1/`nbit'{
|
||
|
|
forvalues j=1/`nbmoda_`ii''{
|
||
|
|
local countbase=`countbase'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues s=1/`nbscore'{
|
||
|
|
local countbase=`countbase'+1
|
||
|
|
}
|
||
|
|
tempname DGibase
|
||
|
|
matrix `DGibase'=J(6,`countbase',.)
|
||
|
|
use `bdd_seg', replace
|
||
|
|
local countbase=0
|
||
|
|
forvalues ii=1/`nbit'{
|
||
|
|
tab it`ii', gen(i`ii'c)
|
||
|
|
forvalues j=1/`nbmoda_`ii''{
|
||
|
|
local countbase=`countbase'+1
|
||
|
|
matrix `DGibase'[2,`countbase']=`ii'
|
||
|
|
matrix `DGibase'[3,`countbase']=`j'
|
||
|
|
su i`ii'c`j'
|
||
|
|
matrix `DGibase'[4,`countbase']=r(sum)
|
||
|
|
}
|
||
|
|
drop i`ii'c*
|
||
|
|
}
|
||
|
|
tab score, gen(s)
|
||
|
|
forvalues s=1/`nbscore'{
|
||
|
|
capture su s`s'
|
||
|
|
if _rc!=0{
|
||
|
|
gen s`s'=0
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues s=1/`nbscore'{
|
||
|
|
local countbase=`countbase'+1
|
||
|
|
matrix `DGibase'[2,`countbase']=`s'
|
||
|
|
su s`s'
|
||
|
|
matrix `DGibase'[4,`countbase']=r(sum)
|
||
|
|
}
|
||
|
|
use `matU2', replace
|
||
|
|
local countbase=0
|
||
|
|
forvalues ii=1/`nbit'{
|
||
|
|
forvalues j=1/`nbmoda_`ii''{
|
||
|
|
local countbase=`countbase'+1
|
||
|
|
su P if i`ii'c`j'==1
|
||
|
|
matrix `DGibase'[5,`countbase']=r(sum)*`N'
|
||
|
|
matrix `DGibase'[6,`countbase']=(`DGibase'[4,`countbase']-`DGibase'[5,`countbase'])/sqrt(`N')
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues s=1/`nbscore'{
|
||
|
|
local countbase=`countbase'+1
|
||
|
|
su P if score`s'==1
|
||
|
|
matrix `DGibase'[5,`countbase']=r(sum)*`N'
|
||
|
|
matrix `DGibase'[6,`countbase']=(`DGibase'[4,`countbase']-`DGibase'[5,`countbase'])/sqrt(`N')
|
||
|
|
}
|
||
|
|
local colbase=`countbase'
|
||
|
|
}
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
tempfile mU2_`i' mU_`i'
|
||
|
|
noi di in gr "Performing Si test for the `i'th item"
|
||
|
|
qui{
|
||
|
|
use `matU2', replace
|
||
|
|
gen g=.
|
||
|
|
local liminf1=-1
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
replace g=`g' if score<=`limsup`g'' & score>`liminf`g''
|
||
|
|
}
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
gen testi`i'c`j'g`g'=0
|
||
|
|
replace testi`i'c`j'g`g'=i`i'c`j' if g==`g'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local count=1
|
||
|
|
forvalues ii=1/`nbit'{
|
||
|
|
forvalues j=1/`nbmoda_`ii''{
|
||
|
|
rename i`ii'c`j' v`count'b
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues s=1/`=`nbscore'+1'{
|
||
|
|
capture rename score`s' v`count'b
|
||
|
|
if _rc ==0{
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
rename testi`i'c`j'g`g' v`count'b
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local nbarrive`i'=`count'-1
|
||
|
|
sort `sort'
|
||
|
|
save `mU2_`i'', replace
|
||
|
|
use `matU1', replace
|
||
|
|
gen g=.
|
||
|
|
local liminf1=-1
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
replace g=`g' if score<=`limsup`g'' & score>`liminf`g''
|
||
|
|
}
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
gen testi`i'c`j'g`g'=0
|
||
|
|
replace testi`i'c`j'g`g'=i`i'c`j' if g==`g'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local count=1
|
||
|
|
forvalues ii=1/`nbit'{
|
||
|
|
forvalues j=1/`nbmoda_`ii''{
|
||
|
|
rename i`ii'c`j' v`count'
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues s=1/`=`nbscore'+1'{
|
||
|
|
capture rename score`s' v`count'
|
||
|
|
if _rc ==0{
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
rename testi`i'c`j'g`g' v`count'
|
||
|
|
local count=`count'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
sort `sort'
|
||
|
|
merge `sort' using `mU2_`i''
|
||
|
|
drop _merge
|
||
|
|
if `nbarrive`i''>r(matsize) & `nbarrive`i''<=r(m_matsize){
|
||
|
|
set matsize `nbarrive`i''
|
||
|
|
}
|
||
|
|
if `nbarrive`i''>r(m_matsize){
|
||
|
|
noi di in red "Error, not enought memory to allocate to the W matrix computation"
|
||
|
|
}
|
||
|
|
tempname i`i'W
|
||
|
|
matrix `i`i'W'=J(`nbarrive`i'',`nbarrive`i'',0)
|
||
|
|
if `=`nbarrive`i''*`nbarrive`i'''>3000{
|
||
|
|
noi di in gr "----|---25%---|---50%---|---75%---|---100%
|
||
|
|
qui _dots 0, title(Loop computation of theorical probabilities of each response pattern) reps(40)
|
||
|
|
local percentcount=0
|
||
|
|
local countS=1
|
||
|
|
}
|
||
|
|
forvalues ii=1/`nbarrive`i''{
|
||
|
|
su v`ii'
|
||
|
|
if r(max)>=0.000001{
|
||
|
|
forvalues j=1/`nbarrive`i''{
|
||
|
|
gen prod=v`ii'*v`j'b
|
||
|
|
qui su prod
|
||
|
|
matrix `i`i'W'[`ii',`j']=r(sum)
|
||
|
|
drop prod
|
||
|
|
if `=`nbarrive`i''*`nbarrive`i'''>3000{
|
||
|
|
local percentcountplus=floor(`countS'*40/`=`nbarrive`i''*`nbarrive`i''')
|
||
|
|
forvalues percen=`=`percentcount'+1'/`percentcountplus'{
|
||
|
|
nois _dots `percen' 0
|
||
|
|
}
|
||
|
|
local percentcount=`percentcountplus'
|
||
|
|
local countS=`countS'+1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
if `=`nbarrive`i''*`nbarrive`i'''>3000{
|
||
|
|
local percentcountplus=floor((`countS'+`nbarrive`i''-1)*40/`=`nbarrive`i''*`nbarrive`i''')
|
||
|
|
forvalues percen=`=`percentcount'+1'/`percentcountplus'{
|
||
|
|
nois _dots `percen' 0
|
||
|
|
}
|
||
|
|
local percentcount=`percentcountplus'
|
||
|
|
local countS=`countS'+`nbarrive`i''
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if `=`nbarrive`i''*`nbarrive`i'''>3000{
|
||
|
|
noi di ""
|
||
|
|
}
|
||
|
|
tempname i`i'Wi
|
||
|
|
capture matrix `i`i'Wi'=invsym(`i`i'W')
|
||
|
|
if _rc!=0{
|
||
|
|
capture matrix `i`i'Wi'=inv(`i`i'W')
|
||
|
|
}
|
||
|
|
if _rc!=0{
|
||
|
|
noi di in red "Error while computing the Wg matrix"
|
||
|
|
}
|
||
|
|
tempname A rank_
|
||
|
|
mata: `A'=J(1,1,.)
|
||
|
|
mata: `A'[1,1]=rank(st_matrix("`i`i'W'"))
|
||
|
|
mata: st_matrix("`rank_'",`A')
|
||
|
|
local i`i'rank=`rank_'[1,1]
|
||
|
|
tempname plus`i' DGi_`i' DGi`i'_a DGi`i'_b DGi_`i'_v2
|
||
|
|
matrix `plus`i''=J(6,`=`nbarrive`i''-`colbase'',.)
|
||
|
|
matrix `DGi_`i''=`DGibase',`plus`i''
|
||
|
|
matrix `DGi`i'_a'=J(1,`=colsof(`DGibase')',0)
|
||
|
|
matrix `DGi`i'_b'=J(1,`=`nbarrive`i''-`colbase'',.)
|
||
|
|
matrix `DGi_`i'_v2'=`DGi`i'_a',`DGi`i'_b'
|
||
|
|
save `mU_`i'', replace
|
||
|
|
local count=`colbase'
|
||
|
|
use `bdd_seg', replace
|
||
|
|
tab it`i', gen(i`i'c)
|
||
|
|
forvalues g=1/`nbgroup'{
|
||
|
|
forvalues j=1/`nbmoda_`i''{
|
||
|
|
local count=`count'+1
|
||
|
|
matrix `DGi_`i''[2,`count']=`i'
|
||
|
|
matrix `DGi_`i''[3,`count']=`j'
|
||
|
|
matrix `DGi_`i''[1,`count']=`g'
|
||
|
|
su i`i'c`j' if g==`g'
|
||
|
|
matrix `DGi_`i''[4,`count']=r(sum)
|
||
|
|
}
|
||
|
|
}
|
||
|
|
use `mU_`i'', replace
|
||
|
|
forvalues t=`=`colbase'+1'/`nbarrive`i''{
|
||
|
|
su P if v`t'b==1
|
||
|
|
matrix `DGi_`i''[5,`t']=r(sum)*`N'
|
||
|
|
matrix `DGi_`i''[6,`t']=(`DGi_`i''[4,`t']-`DGi_`i''[5,`t'])/sqrt(`N')
|
||
|
|
matrix `DGi_`i'_v2'[1,`t']=(`DGi_`i''[4,`t']-`DGi_`i''[5,`t'])/sqrt(`N')
|
||
|
|
}
|
||
|
|
set matsize `matsizeini'
|
||
|
|
tempname tDGi_`i' tDGi_`i'_v2 G G_v2
|
||
|
|
matrix `tDGi_`i''=`DGi_`i''[6,1..`=colsof(`DGi_`i'')']'
|
||
|
|
matrix `tDGi_`i'_v2'=`DGi_`i'_v2''
|
||
|
|
matrix `G'=`tDGi_`i'''*`i`i'Wi'*`tDGi_`i''
|
||
|
|
matrix `G_v2'=`tDGi_`i'_v2''*`i`i'Wi'*`tDGi_`i'_v2'
|
||
|
|
local sum=`G'[1,1]
|
||
|
|
local sum_v2=`G_v2'[1,1]
|
||
|
|
local rank "`i`i'rank'"
|
||
|
|
local ddl=(`nbgroup'-1)*(`nbmoda_`i''-1)
|
||
|
|
}
|
||
|
|
local S`i'_rank=`rank'
|
||
|
|
local S`i'_ddl=`ddl'
|
||
|
|
local S`i'_stat=`sum'*`propFit'
|
||
|
|
local S`i'_p=`=1-chi2(`S`i'_ddl', `S`i'_stat')'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
/* Graphs : */
|
||
|
|
|
||
|
|
if "`graphics'"!=""{
|
||
|
|
noi di ""
|
||
|
|
noi di ""
|
||
|
|
noi di in gr "Graphics:"
|
||
|
|
tempfile graph
|
||
|
|
qui{
|
||
|
|
local debut=1
|
||
|
|
local fin=1
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
local fin=`fin'+`nbmoda_`i''-2
|
||
|
|
tempname it`i'
|
||
|
|
matrix `it`i''=`Edelta'[1,`debut'..`fin']
|
||
|
|
local fin=`fin'+1
|
||
|
|
local debut=`debut'+`nbmoda_`i''-1
|
||
|
|
}
|
||
|
|
clear
|
||
|
|
use `bdd_se', replace
|
||
|
|
local scmin=1
|
||
|
|
local scmax=-1
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
local scmax=`scmax'+`nbmoda_`i''-1
|
||
|
|
}
|
||
|
|
gen select=score<=`scmin'
|
||
|
|
su score if select==1
|
||
|
|
local scorereel_scmin=r(mean)
|
||
|
|
replace select=score>=`scmax'
|
||
|
|
su score if select==1
|
||
|
|
local scorereel_scmax=r(mean)
|
||
|
|
replace score=`scmin' if score<`scmin'
|
||
|
|
replace score=`scmax' if score>`scmax'
|
||
|
|
tab score, matcell(matname)
|
||
|
|
local tottab=r(N)
|
||
|
|
clear
|
||
|
|
set obs 2000
|
||
|
|
gen theta=_n/100-10
|
||
|
|
gen scoreth=0
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
tempname D`i'
|
||
|
|
matrix `D`i''=J(1,`nbmoda_`i'',0)
|
||
|
|
gen eV`i'_0=1
|
||
|
|
gen SeV`i'=1
|
||
|
|
forvalues j=1/`=`nbmoda_`i''-1'{
|
||
|
|
matrix `D`i''[1,`=`j'+1']=`it`i''[1,`j']+`D`i''[1,`j']
|
||
|
|
gen eV`i'_`j'=exp(`j'*theta-`D`i''[1,`=`j'+1'])
|
||
|
|
replace SeV`i'=SeV`i'+eV`i'_`j'
|
||
|
|
}
|
||
|
|
gen p`i'_0=eV`i'_0/SeV`i'
|
||
|
|
forvalues j=1/`=`nbmoda_`i''-1'{
|
||
|
|
gen p`i'_`j'=eV`i'_`j'/SeV`i'
|
||
|
|
replace scoreth=scoreth+(eV`i'_`j'/SeV`i')*`j'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
drop e* S* p*
|
||
|
|
su scoreth
|
||
|
|
local scmin=ceil(r(min))
|
||
|
|
local scmax=floor(r(max))
|
||
|
|
gen sc=abs(scoreth-`scorereel_scmin')
|
||
|
|
sort sc
|
||
|
|
local valini_`scmin'=theta[1]
|
||
|
|
drop sc
|
||
|
|
gen sc=abs(scoreth-`scorereel_scmax')
|
||
|
|
sort sc
|
||
|
|
local valini_`scmax'=theta[1]
|
||
|
|
drop sc
|
||
|
|
tempname scoretheta
|
||
|
|
matrix `scoretheta'=J(2,`scmax',.)
|
||
|
|
forvalues i=`=`scmin'+1'/`=`scmax'-1'{
|
||
|
|
matrix `scoretheta'[1,`i']=`i'
|
||
|
|
gen sc=abs(scoreth-`i')
|
||
|
|
sort sc
|
||
|
|
local valini_`i'=theta[1]
|
||
|
|
drop sc
|
||
|
|
}
|
||
|
|
matrix `scoretheta'[1,1]=`scorereel_scmin'
|
||
|
|
matrix `scoretheta'[1,`scmax']=`scorereel_scmax'
|
||
|
|
forvalues i=1/`scmax'{
|
||
|
|
matrix `scoretheta'[2,`i']=`valini_`i''
|
||
|
|
}
|
||
|
|
tempfile graphscthscobstheta
|
||
|
|
save `graphscthscobstheta', replace
|
||
|
|
clear
|
||
|
|
use `bdd_se', replace
|
||
|
|
gen select=score<=`scmin'
|
||
|
|
su score if select==1
|
||
|
|
local scorereel_scmin=r(mean)
|
||
|
|
replace select=score>=`scmax'
|
||
|
|
su score if select==1
|
||
|
|
local scorereel_scmax=r(mean)
|
||
|
|
replace score=`scmin' if score<`scmin'
|
||
|
|
replace score=`scmax' if score>`scmax'
|
||
|
|
drop g
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
gen rep`i' = it`i'
|
||
|
|
drop it`i'
|
||
|
|
}
|
||
|
|
contract rep1-rep`nbit' score, f(wt2)
|
||
|
|
gen id=_n
|
||
|
|
reshape long rep, i(id) j(it)
|
||
|
|
drop if rep==.
|
||
|
|
gen obs=_n
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
expand `nbmoda_`i'' if it==`i'
|
||
|
|
}
|
||
|
|
by obs, sort: gen `x'=_n-1
|
||
|
|
gen choix=rep==`x'
|
||
|
|
rename it item
|
||
|
|
tab item, gen(it)
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
forvalues g=1/`=`nbmoda_`i''-1'{
|
||
|
|
gen d_i`i'_m`g'=(-1)*it`i'*(`x'>=`g')
|
||
|
|
}
|
||
|
|
}
|
||
|
|
gen difficulties=0
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
forvalues g=1/`=`nbmoda_`i''-1'{
|
||
|
|
replace difficulties=difficulties+`it`i''[1,`g']*d_i`i'_m`g'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
tab score, gen(score__) matrow(nom)
|
||
|
|
local nbmodscore=r(r)
|
||
|
|
forvalues k=1/`nbmodscore'{
|
||
|
|
replace score__`k'=`x' if score__`k'==1
|
||
|
|
local ident=nom[`k',1]
|
||
|
|
if `k'==1{
|
||
|
|
local ident1=`ident'
|
||
|
|
}
|
||
|
|
rename score__`k' score_`ident'
|
||
|
|
}
|
||
|
|
eq slope: `x'
|
||
|
|
noi di in gr "Performing graphics"
|
||
|
|
use `graphscthscobstheta', replace
|
||
|
|
gen sc=abs(scoreth-`scorereel_scmin')
|
||
|
|
sort sc
|
||
|
|
local limginf=theta[1]-1.5
|
||
|
|
drop sc
|
||
|
|
gen sc=abs(scoreth-`scorereel_scmax')
|
||
|
|
sort sc
|
||
|
|
local limgsup=theta[1]+1.5
|
||
|
|
drop sc
|
||
|
|
drop if theta<`limginf' | theta>`limgsup'
|
||
|
|
capture graph drop Obs_vs_Exp_LT
|
||
|
|
capture graph drop MAP
|
||
|
|
capture graph drop Score_Distrib
|
||
|
|
capture graph drop Contrib
|
||
|
|
twoway (line scoreth theta, sort) , ytitle(Score) xtitle(Latent trait) title("Expected scores depending on individual latent traits", size(medium)) scheme(s2mono) graphregion(fcolor(white) ifcolor(white)) name("LT_Sc", replace)
|
||
|
|
tempfile gEO
|
||
|
|
graph save `gEO', replace
|
||
|
|
if "`filegraph'"!=""{
|
||
|
|
graph save "`filegraph'_LT_Sc", replace
|
||
|
|
}
|
||
|
|
clear
|
||
|
|
set obs `=int(`=rowsof(matname)+colsof(`Edelta')'+0.1)'
|
||
|
|
gen theta=.
|
||
|
|
gen diff=0
|
||
|
|
gen freq=.
|
||
|
|
forvalues i=1/`=rowsof(matname)'{
|
||
|
|
replace theta=`scoretheta'[2,`i'] if _n==`i'
|
||
|
|
replace freq=matname[`i',1]/`tottab' if _n==`i'
|
||
|
|
}
|
||
|
|
su freq
|
||
|
|
local tadatzouinzou=-r(max)/8
|
||
|
|
forvalues i=1/`=colsof(`Edelta')'{
|
||
|
|
replace theta=`Edelta'[1,`i'] if _n==`i'+`=rowsof(matname)'
|
||
|
|
replace freq=`tadatzouinzou' if _n==`i'+`=rowsof(matname)'
|
||
|
|
replace diff=1 if _n==`i'+`=rowsof(matname)'
|
||
|
|
}
|
||
|
|
sort diff theta
|
||
|
|
bysort diff: replace freq=freq-(`tadatzouinzou'/5) if theta<theta[_n-1]+0.08 & diff==1 & _n!=1
|
||
|
|
replace theta=round(theta,0.01)
|
||
|
|
compress
|
||
|
|
sort theta
|
||
|
|
save `graph', replace
|
||
|
|
su theta
|
||
|
|
local mininf=round(`=r(min)-(r(max)-r(min))/4',0.01)
|
||
|
|
local maxinf=round(`=r(max)+(r(max)-r(min))/4',0.01)
|
||
|
|
clear
|
||
|
|
set obs `=int(`=(`maxinf'-`mininf')*100'+0.1)'
|
||
|
|
gen theta=round(_n/100+`mininf',0.01)
|
||
|
|
compress
|
||
|
|
sort theta
|
||
|
|
merge theta using `graph'
|
||
|
|
drop _merge
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
tempname D`i'
|
||
|
|
matrix `D`i''=J(1,`nbmoda_`i'',0)
|
||
|
|
gen eV`i'_0=1
|
||
|
|
gen SeV`i'=1
|
||
|
|
forvalues j=1/`=`nbmoda_`i''-1'{
|
||
|
|
matrix `D`i''[1,`=`j'+1']=`it`i''[1,`j']+`D`i''[1,`j']
|
||
|
|
gen eV`i'_`j'=exp(`j'*theta-`D`i''[1,`=`j'+1'])
|
||
|
|
replace SeV`i'=SeV`i'+eV`i'_`j'
|
||
|
|
}
|
||
|
|
gen p`i'_0=eV`i'_0/SeV`i'
|
||
|
|
forvalues j=1/`=`nbmoda_`i''-1'{
|
||
|
|
gen p`i'_`j'=eV`i'_`j'/SeV`i' + p`i'_`=`j'-1'
|
||
|
|
}
|
||
|
|
drop eV* SeV*
|
||
|
|
}
|
||
|
|
gen L=1
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
forvalues j=0/`=`nbmoda_`i''-1'{
|
||
|
|
replace L=L*p`i'_`j'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
sort theta
|
||
|
|
replace L=ln(L)
|
||
|
|
gen d1=.
|
||
|
|
replace d1=(L-L[_n-1])/(theta-theta[_n-1]) if _n>1
|
||
|
|
gen d2=.
|
||
|
|
replace d2=(d1-d1[_n-1])/(theta-theta[_n-1]) if _n>1
|
||
|
|
replace d2=-d2
|
||
|
|
su freq
|
||
|
|
local freqmin=r(min)
|
||
|
|
local freqmax=r(max)
|
||
|
|
su d2
|
||
|
|
local d2max=r(max)
|
||
|
|
local d2min=`d2max'*`freqmax'/`freqmin'
|
||
|
|
label variable freq "Freq. (%)"
|
||
|
|
label variable d2 "Information"
|
||
|
|
sort theta
|
||
|
|
twoway (spike freq theta if diff==0, lwidth(thick) horizontal xscale(alt axis(1)) ) (scatter theta freq if diff==1,mcolor(black) msymbol(plus)) (line theta d2, xaxis(2) xscale(alt axis(2))) , yscale(noline) ylabel(#5, angle(horizontal)) xscale(range(`freqmin' `freqmax') axis(1)) xscale(reverse range(`d2min' `d2max') axis(2)) yscale(range(`mininf' `maxinf')) xline(0) xlabel(0 (0.05) `freqmax') title(, size(medium)) legend(order(1 "Persons" 2 "Thresholds location" 3 "Information curve") cols(1) size(small)) scheme(s2mono) graphregion(fcolor(white) ifcolor(white)) ytitle(Latent trait) title(MAP) name("MAP", replace)
|
||
|
|
tempfile gMAP
|
||
|
|
graph save `gMAP', replace
|
||
|
|
if "`filegraph'"!=""{
|
||
|
|
graph save "`filegraph'_MAP", replace
|
||
|
|
}
|
||
|
|
clear
|
||
|
|
use "`dataR1m'"
|
||
|
|
keep score P
|
||
|
|
collapse (sum) P, by(score)
|
||
|
|
sort score
|
||
|
|
save `bdd_G', replace
|
||
|
|
clear
|
||
|
|
use "`datatest'"
|
||
|
|
keep `varlist'
|
||
|
|
tempname dm SumScore
|
||
|
|
egen `dm'=rowmiss(`varlist')
|
||
|
|
replace `dm'=`dm'>0
|
||
|
|
keep if `dm'==0
|
||
|
|
tempname SumScore
|
||
|
|
egen `SumScore'=rowtotal(`varlist')
|
||
|
|
gen Pobs=1
|
||
|
|
rename `SumScore' score
|
||
|
|
keep Pobs score
|
||
|
|
local tot=_N
|
||
|
|
collapse (sum) Pobs, by(score)
|
||
|
|
replace Pobs=Pobs/`tot'
|
||
|
|
sort score
|
||
|
|
merge 1:1 score using `bdd_G'
|
||
|
|
gen g=.
|
||
|
|
drop _merge
|
||
|
|
sort g
|
||
|
|
save `bdd_G', replace
|
||
|
|
clear
|
||
|
|
svmat `graphContribPond'
|
||
|
|
rename `graphContribPond'1 g
|
||
|
|
rename `graphContribPond'2 Contrib
|
||
|
|
sort g
|
||
|
|
merge g using `bdd_G'
|
||
|
|
su Contrib
|
||
|
|
replace Contrib=Contrib/r(sum)
|
||
|
|
capture label drop g
|
||
|
|
local liminf1=-1
|
||
|
|
forvalues i=1/`nbgroup'{
|
||
|
|
local limsup`i'=real("`=word("`list'",`i')'")
|
||
|
|
if `i'>1{
|
||
|
|
local liminf`i'=real("`=word("`list'",`=`i'-1')'")
|
||
|
|
}
|
||
|
|
replace g=`i' if score<=`limsup`i'' & score>`liminf`i''
|
||
|
|
if `i'==1{
|
||
|
|
label define g `i' "[0;`limsup`i'']"
|
||
|
|
}
|
||
|
|
else if `i' == `nbgroup'{
|
||
|
|
label define g `i' "]`liminf`i'';`=`nbscore'-1']", a
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
label define g `i' "]`liminf`i'';`limsup`i'']", a
|
||
|
|
}
|
||
|
|
}
|
||
|
|
label values g g
|
||
|
|
gen nb=P*`EN'
|
||
|
|
su score [iweight=nb]
|
||
|
|
local MoyThScore=r(mean)
|
||
|
|
local SdThScore=r(sd)
|
||
|
|
gen nbObs=Pobs*`EN'
|
||
|
|
su score [iweight=nbObs]
|
||
|
|
local MoyObsScore=r(mean)
|
||
|
|
local SdObdcore=r(sd)
|
||
|
|
drop _merge
|
||
|
|
tempfile BDD
|
||
|
|
sort score
|
||
|
|
save `BDD', replace
|
||
|
|
clear
|
||
|
|
set obs `=(`=r(max)'+2)*100'
|
||
|
|
gen score=(_n/100)-1
|
||
|
|
gen p=normalden(score,`MoyThScore',`SdThScore')
|
||
|
|
gen pobs=normalden(score,`MoyObsScore',`SdObdcore')
|
||
|
|
sort score
|
||
|
|
merge score using `BDD'
|
||
|
|
gen score1=score if Pobs!=.
|
||
|
|
gen scorep=score1-0.15
|
||
|
|
gen scorep2=score1+0.15
|
||
|
|
twoway (bar Pobs scorep, horizontal barwidth(0.3)) (bar P scorep2, horizontal barwidth(0.3)) (line score p, lpattern(solid)lcolor(black)) (line score pobs, lpattern(vshortdash) lcolor(gs12)), yscale(reverse) scheme(s2mono) xtitle(%) xscale(range(0 0.01)) xlabel(#5) legend(order(1 "% observed" 3 "" 2 "% expected" 4 "") cols(2) size(small)) title("Observed and expected" "scores distribution", size(medium)) graphregion(fcolor(white)) name("Score_Distrib", replace)
|
||
|
|
tempfile gTS
|
||
|
|
graph save `gTS', replace
|
||
|
|
if "`filegraph'"!=""{
|
||
|
|
graph save "`filegraph'_totscore", replace
|
||
|
|
}
|
||
|
|
graph hbar (sum) Pobs P Contrib, over(g) yvaroptions(relabel(1 "% observed" 2 "% expected" 3 "% R1m contribution") label(labcolor(none) labsize(zero))) title("Groups contribution to" "the R1m statistic", size(medium)) legend(cols(1) size(small)) ytitle("%") scheme(s2mono) graphregion(fcolor(white)) bar(3, fcolor(black)) bar(1, fcolor(gs8)) bar(2, fcolor(gs13)) name("Contrib", replace)
|
||
|
|
tempfile gSG
|
||
|
|
graph save `gSG', replace
|
||
|
|
if "`filegraph'"!=""{
|
||
|
|
graph save "`filegraph'_scoregp", replace
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
tempname globalFit itemFit
|
||
|
|
matrix `globalFit'=(`R1M_stat',`R1M_ddl',`R1M_p')
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix itemFit=J(`nbit',3,.)
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
matrix itemFit[`i',1]=`S`i'_stat'
|
||
|
|
matrix itemFit[`i',2]=`S`i'_ddl'
|
||
|
|
matrix itemFit[`i',3]=`S`i'_p'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`alpha'"==""{
|
||
|
|
local alpha=0.05
|
||
|
|
}
|
||
|
|
tempname g it r Power bB cC Discriminant
|
||
|
|
matrix `g'=`globalFit'
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix `it'=itemFit
|
||
|
|
}
|
||
|
|
if "`nfit'"==""{
|
||
|
|
local `r'=1
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local `r'=`NbIdFit'/`nfit'
|
||
|
|
}
|
||
|
|
local `g'_t=`g'[1,1]*``r''
|
||
|
|
if `g'[1,2]<=200{
|
||
|
|
local `Power'_t_R1m= 1-nchi2(`g'[1,2],``g'_t',invchi2tail(`g'[1,2],`alpha'))
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local `Power'_t_R1m=1-(normal((invchi2tail(`g'[1,2],`alpha')-(`g'[1,2]+``g'_t'))/sqrt(2*(`g'[1,2]+2*``g'_t'))))
|
||
|
|
}
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
local `it'_`i'_t=`it'[`i',1]*``r''
|
||
|
|
if `it'[`i',2]>200 | ``it'_`i'_t'>1000{
|
||
|
|
local `Power'_t_S`i'=1-(normal((invchi2tail(`it'[`i',2],`alpha')-(`it'[`i',2]+``it'_`i'_t'))/sqrt(2*(`it'[`i',2]+2*``it'_`i'_t'))))
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local `Power'_t_S`i'= 1-nchi2(`it'[`i',2],``it'_`i'_t',invchi2tail(`it'[`i',2],`alpha'))
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`nfit'"!=""{
|
||
|
|
local `r'_2=``r''*`nfit'/`NbIdFit'
|
||
|
|
local `g'_newN=`g'[1,1]*``r'_2'
|
||
|
|
if `g'[1,2]<=200{
|
||
|
|
local `Power'_newN_R1m= 1-nchi2(`g'[1,2],``g'_newN',invchi2tail(`g'[1,2],`alpha'))
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local `Power'_newN_R1m=1-(normal((invchi2tail(`g'[1,2],`alpha')-(`g'[1,2]+``g'_newN'))/sqrt(2*(`g'[1,2]+2*``g'_newN'))))
|
||
|
|
}
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
local `it'_`i'_newN=`it'[`i',1]*``r'_2'
|
||
|
|
if `it'[`i',2]>200 | ``it'_`i'_newN'>1000{
|
||
|
|
local `Power'_newN_S`i'=1-(normal((invchi2tail(`it'[`i',2],`alpha')-(`it'[`i',2]+``it'_`i'_newN'))/sqrt(2*(`it'[`i',2]+2*``it'_`i'_newN'))))
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local `Power'_newN_S`i'= 1-nchi2(`it'[`i',2],``it'_`i'_newN',invchi2tail(`it'[`i',2],`alpha'))
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`power'"!=""{
|
||
|
|
if `g'[1,2]<=200{
|
||
|
|
local `g'_newP=npnchi2(`=`g'[1,2]',`=invchi2tail(`=`g'[1,2]',`alpha')',`=1-`power'')
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local `bB'=2*`=`g'[1,2]'-2*`=invchi2tail(`=`g'[1,2]',`alpha')'-4*(invnormal(`=1-0.8'))^2
|
||
|
|
local `cC'=(`=invchi2tail(`=`g'[1,2]',`alpha')')^2-2*`=`g'[1,2]'*`=invchi2tail(`=`g'[1,2]',`alpha')'+(`=`g'[1,2]')^2-2*`=`g'[1,2]'*(invnormal(`=1-0.8'))^2
|
||
|
|
local `Discriminant'=(``bB'')^2-4*``cC''
|
||
|
|
local `g'_newP=(sqrt(``Discriminant'')-``bB'')/2
|
||
|
|
}
|
||
|
|
local `r'_3=``g'_newP'/``g'_t'
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
local `it'_`i'_newP=``it'_`i'_t'*``r'_3'
|
||
|
|
if `it'[`i',2]>200 | ``it'_`i'_newP'>1000{
|
||
|
|
local `Power'_newP_S`i'=1-(normal((invchi2tail(`it'[`i',2],`alpha')-(`it'[`i',2]+``it'_`i'_newP'))/sqrt(2*(`it'[`i',2]+2*``it'_`i'_newP'))))
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local `Power'_newP_S`i'= 1-nchi2(`it'[`i',2],``it'_`i'_newP',invchi2tail(`it'[`i',2],`alpha'))
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************/
|
||
|
|
/* print */
|
||
|
|
/*************************************/
|
||
|
|
|
||
|
|
di ""
|
||
|
|
di ""
|
||
|
|
di in gr "Global tests of the fit : test R1m"
|
||
|
|
di in gr " groups : " in ye "`R1m_group'"
|
||
|
|
di in gr " Number of individuals with missing data : " in ye "`nbmissing' " in gr "(" in ye "`=round(`=`percentmissing'*100',0.01)'%" in gr ")"
|
||
|
|
di ""
|
||
|
|
if "`nfit'"!="" & "`power'"!=""{
|
||
|
|
di in gr "{hline 90}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit' _col(53) in gr "N = " in ye %6.0f `nfit' _col(76) in gr "N = " in ye %6.0f `=ceil(`NbIdFit'*``r'_3')'
|
||
|
|
di _col(16) in gr "df" _col(26) in gr "R1m" _col(32) in gr "p-val" _col(39) in gr "Power" _col(49) in gr "R1m" _col(55) in gr "p-val" _col(62) in gr "Power" _col(72) in gr "R1m" _col(78) in gr "p-val" _col(85) in gr "Power"
|
||
|
|
di in gr "{hline 90}"
|
||
|
|
di _col(3) in gr "R1m" _col(14) in ye %4.0f `R1M_ddl' _col(23) in ye %6.1f ``g'_t' _col(32) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_t')' _col(39) in ye %5.4f ``Power'_t_R1m' _col(46) in ye %6.1f ``g'_newN' _col(55) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_newN')' _col(62) in ye %5.4f ``Power'_newN_R1m' _col(69) in ye %6.1f ``g'_newP' _col(78) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_newP')' _col(85) in ye %5.4f `power'
|
||
|
|
di in gr "{hline 90}"
|
||
|
|
di in gr ""
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
di in gr "Items specific tests of the fit : tests Si"
|
||
|
|
di in gr ""
|
||
|
|
di in gr "{hline 90}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit' _col(53) in gr "N = " in ye %6.0f `nfit' _col(76) in gr "N = " in ye %6.0f `=ceil(`NbIdFit'*``r'_3')'
|
||
|
|
di _col(1) in gr "Item" _col(16) in gr "df" _col(27) in gr "Si" _col(32) in gr "p-val" _col(39) in gr "Power" _col(50) in gr "Si" _col(55) in gr "p-val" _col(62) in gr "Power" _col(73) in gr "Si" _col(78) in gr "p-val" _col(85) in gr "Power"
|
||
|
|
di in gr "{hline 90}"
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
di _col(1) in gr "``i'' :" _col(14) in ye %4.0f `S`i'_ddl' _col(23) in ye %6.1f ``it'_`i'_t' _col(32) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_t')' _col(39) in ye %5.4f ``Power'_t_S`i'' _col(46) in ye %6.1f ``it'_`i'_newN' _col(55) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_newN')' _col(62) in ye %5.4f ``Power'_newN_S`i'' _col(69) in ye %6.1f ``it'_`i'_newP' _col(78) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_newP')' _col(85) in ye %5.4f ``Power'_newP_S`i''
|
||
|
|
di in gr "{hline 90}"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else if "`nfit'"!=""{
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit' _col(53) in gr "N = " in ye %6.0f `nfit'
|
||
|
|
di _col(16) in gr "df" _col(26) in gr "R1m" _col(32) in gr "p-val" _col(39) in gr "Power" _col(49) in gr "R1m" _col(55) in gr "p-val" _col(62) in gr "Power"
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di _col(3) in gr "R1m" _col(14) in ye %4.0f `R1M_ddl' _col(23) in ye %6.1f ``g'_t' _col(32) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_t')' _col(39) in ye %5.4f ``Power'_t_R1m' _col(46) in ye %6.1f ``g'_newN' _col(55) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_newN')' _col(62) in ye %5.4f ``Power'_newN_R1m'
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di in gr ""
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
di in gr "Items specific tests of the fit : tests Si"
|
||
|
|
di in gr ""
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit' _col(53) in gr "N = " in ye %6.0f `nfit'
|
||
|
|
di _col(1) in gr "Item" _col(17) in gr "df" _col(26) in gr "Si" _col(32) in gr "p-val" _col(39) in gr "Power" _col(50) in gr "Si" _col(55) in gr "p-val" _col(62) in gr "Power"
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
di _col(1) in gr "``i'' :" _col(14) in ye %4.0f `S`i'_ddl' _col(23) in ye %6.1f ``it'_`i'_t' _col(32) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_t')' _col(39) in ye %5.4f ``Power'_t_S`i'' _col(46) in ye %6.1f ``it'_`i'_newN' _col(55) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_newN')' _col(62) in ye %5.4f ``Power'_newN_S`i''
|
||
|
|
di in gr "{hline 90}"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else if "`power'"!=""{
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit' _col(53) in gr "N = " in ye %6.0f `=ceil(`NbIdFit'*``r'_3')'
|
||
|
|
di _col(16) in gr "df" _col(26) in gr "R1m" _col(32) in gr "p-val" _col(39) in gr "Power" _col(49) in gr "R1m" _col(55) in gr "p-val" _col(62) in gr "Power"
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di _col(3) in gr "R1m" _col(14) in ye %4.0f `R1M_ddl' _col(23) in ye %6.1f ``g'_t' _col(32) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_t')' _col(39) in ye %5.4f ``Power'_t_R1m' _col(46) in ye %6.1f ``g'_newP' _col(55) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_newP')' _col(62) in ye %5.4f `power'
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di in gr ""
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
di in gr "Items specific tests of the fit : tests Si"
|
||
|
|
di in gr ""
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit' _col(53) in gr "N = " in ye %6.0f `=ceil(`NbIdFit'*``r'_3')'
|
||
|
|
di _col(1) in gr "Item" _col(16) in gr "df" _col(27) in gr "Si" _col(32) in gr "p-val" _col(39) in gr "Power" _col(50) in gr "Si" _col(55) in gr "p-val" _col(62) in gr "Power"
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
di _col(1) in gr "``i'' :" _col(14) in ye %4.0f `S`i'_ddl' _col(23) in ye %6.1f ``it'_`i'_t' _col(32) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_t')' _col(39) in ye %5.4f ``Power'_t_S`i'' _col(46) in ye %6.1f ``it'_`i'_newP' _col(55) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_newP')' _col(62) in ye %5.4f ``Power'_newP_S`i''
|
||
|
|
di in gr "{hline 67}"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
di in gr "{hline 44}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit'
|
||
|
|
di _col(16) in gr "df" _col(26) in gr "R1m" _col(32) in gr "p-val" _col(39) in gr "Power"
|
||
|
|
di in gr "{hline 44}"
|
||
|
|
di _col(3) in gr "R1m" _col(14) in ye %4.0f `R1M_ddl' _col(23) in ye %6.1f ``g'_t' _col(32) in ye %5.4f `=1-chi2(`=`g'[1,2]', ``g'_t')' _col(39) in ye %5.4f ``Power'_t_R1m'
|
||
|
|
di in gr "{hline 44}"
|
||
|
|
di in gr ""
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
di in gr "Items specific tests of the fit : tests Si"
|
||
|
|
di in gr ""
|
||
|
|
di in gr "{hline 44}"
|
||
|
|
di _col(30) in gr "N = " in ye %6.0f `NbIdFit'
|
||
|
|
di _col(1) in gr "Item" _col(16) in gr "df" _col(27) in gr "Si" _col(32) in gr "p-val" _col(39) in gr "Power"
|
||
|
|
di in gr "{hline 44}"
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
di _col(1) in gr "``i'' :" _col(14) in ye %4.0f `S`i'_ddl' _col(23) in ye %6.1f ``it'_`i'_t' _col(32) in ye %5.4f `=1-chi2(`=`it'[`i',2]', ``it'_`i'_t')' _col(39) in ye %5.4f ``Power'_t_S`i''
|
||
|
|
di in gr "{hline 44}"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************/
|
||
|
|
/* ereturn */
|
||
|
|
/*************************************/
|
||
|
|
|
||
|
|
|
||
|
|
return clear
|
||
|
|
if "`nfit'"!=""{
|
||
|
|
return scalar NumFit=`nfit'
|
||
|
|
tempname globalFitNu itemFitNu
|
||
|
|
matrix `globalFitNu'=(``g'_newN',`R1M_ddl',`=1-chi2(`=`g'[1,2]', ``g'_newN')',``Power'_newN_R1m',`nfit')
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix `itemFitNu'=J(`nbit',5,.)
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
matrix `itemFitNu'[`i',1]=``it'_`i'_newN'
|
||
|
|
matrix `itemFitNu'[`i',2]=`S`i'_ddl'
|
||
|
|
matrix `itemFitNu'[`i',3]=`=1-chi2(`=`it'[`i',2]', ``it'_`i'_newN')'
|
||
|
|
matrix `itemFitNu'[`i',4]=``Power'_newN_S`i''
|
||
|
|
matrix `itemFitNu'[`i',5]=`nfit'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
matrix coln `globalFitNu'=R1m df alpha power N
|
||
|
|
matrix rown `globalFitNu'=Global
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix coln `itemFitNu'=Si df alpha power N
|
||
|
|
return matrix itemFitNu=`itemFitNu'
|
||
|
|
}
|
||
|
|
return matrix globalFitNu=`globalFitNu'
|
||
|
|
}
|
||
|
|
if "`power'"!=""{
|
||
|
|
return scalar PowFit=`power'
|
||
|
|
tempname globalFitPo itemFitPo
|
||
|
|
matrix `globalFitPo'=(``g'_newP',`R1M_ddl',`=1-chi2(`=`g'[1,2]', ``g'_newP')',`power',`=ceil(`NbIdFit'*``r'_3')')
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix `itemFitPo'=J(`nbit',5,.)
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
matrix `itemFitPo'[`i',1]=``it'_`i'_newP'
|
||
|
|
matrix `itemFitPo'[`i',2]=`S`i'_ddl'
|
||
|
|
matrix `itemFitPo'[`i',3]=`=1-chi2(`=`it'[`i',2]', ``it'_`i'_newP')'
|
||
|
|
matrix `itemFitPo'[`i',4]=``Power'_newP_S`i''
|
||
|
|
matrix `itemFitPo'[`i',5]=`=ceil(`NbIdFit'*``r'_3')'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
matrix coln `globalFitPo'=R1m df alpha power N
|
||
|
|
matrix rown `globalFitPo'=Global
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix coln `itemFitPo'=Si df alpha power N
|
||
|
|
return matrix itemFitPo=`itemFitPo'
|
||
|
|
}
|
||
|
|
return matrix globalFitPo=`globalFitPo'
|
||
|
|
}
|
||
|
|
tempname globalFitTot itemFitTot
|
||
|
|
matrix `globalFitTot'=(``g'_t',`R1M_ddl',`=1-chi2(`=`g'[1,2]', ``g'_t')',``Power'_t_R1m',`NbIdFit')
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix `itemFitTot'=J(`nbit',5,.)
|
||
|
|
forvalues i=1/`nbit'{
|
||
|
|
matrix `itemFitTot'[`i',1]=``it'_`i'_t'
|
||
|
|
matrix `itemFitTot'[`i',2]=`S`i'_ddl'
|
||
|
|
matrix `itemFitTot'[`i',3]=`=1-chi2(`=`it'[`i',2]', ``it'_`i'_t')'
|
||
|
|
matrix `itemFitTot'[`i',4]=``Power'_t_S`i''
|
||
|
|
matrix `itemFitTot'[`i',5]=`NbIdFit'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
matrix coln `globalFitTot'=R1m df alpha power N
|
||
|
|
matrix rown `globalFitTot'=Global
|
||
|
|
if `nbitsuf'==1 & "`sitest'"!=""{
|
||
|
|
matrix coln `itemFitTot'=Si df alpha power N
|
||
|
|
return matrix itemFitTot=`itemFitTot'
|
||
|
|
}
|
||
|
|
return matrix globalFitTot=`globalFitTot'
|
||
|
|
use `bddtravail', replace
|
||
|
|
restore
|
||
|
|
end
|