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987 lines
33 KiB
Plaintext
987 lines
33 KiB
Plaintext
9 months ago
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*! Version 3.4 23August2019
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*! Jean-Benoit Hardouin
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************************************************************************************************************
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* Stata program : pcm
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* Estimate the parameters of the Partial Credit Model
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* Version 1 : December 17, 2007 [Jean-Benoit Hardouin]
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* Version 2 : July 15, 2011 [Jean-Benoit Hardouin]
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* Version 2.1 : October 18th, 2011 [Jean-Benoit Hardouin] : -fixedvar- option, new presentation
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* Version 2.2 : October 23rd, 2013 [Jean-Benoit Hardouin] : correction of -fixedvar- option
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* Version 2.3 : April 10th, 2014 [Jean-Benoit Hardouin] : correction of -fixedvar- option
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* Version 2.3 : April 10th, 2014 [Jean-Benoit Hardouin] : correction of -fixedvar- option
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* Version 3 : July 6th, 2019 [Jean-Benoit Hardouin] : New version using gsem
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* Version 3.1 : July 9th, 2019 [Jean-Benoit Hardouin] : Small corrections
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* Version 3.2 : July 17th, 2019 [Jean-Benoit Hardouin] : Small corrections
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* Version 3.3 : July 25th, 2019 [Jean-Benoit Hardouin] : -pce- option
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* Version 3.4 : August 23th, 2019 [Jean-Benoit Hardouin] : Correction of a bug
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*
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*
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*
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* Jean-benoit Hardouin - University of Nantes - France
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* INSERM UMR 1246-SPHERE "Methods in Patient Centered Outcomes and Health Research", Nantes University, University of Tours
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* jean-benoit.hardouin@univ-nantes.fr
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*
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* News about this program : http://www.anaqol.org
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*
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* Copyright 2007, 2011, 2013, 2014, 2019 Jean-Benoit Hardouin
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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************************************************************************************************************/
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program define pcm, rclass
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syntax varlist(min=2 numeric) [iweight] [, CONTinuous(varlist) CATegorical(varlist) ITerate(int 100) TOLerance(real 0.01) model DIFFiculties(name) rsm Graphs noGRAPHItems filesave dirsave(string) docx(string) extension(string) PCE WMLiterate(int 1) GENLT(name) GENINF(name) postpce]
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qui count
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local nbobs=r(N)
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/*************************************************************************************************************
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GESTION DES VARIABLES CONTINUES ET CATEGORIELLES
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*************************************************************************************************************/
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local modcont
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local nbpar=0
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local nbcont=0
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local nbcat=0
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if "`continuous'"!="" {
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tokenize `continuous'
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local nbcont : word count `continuous'
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local continuous
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forvalues i=1/`nbcont' {
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local cont`i' ``i''
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local continuous `continuous' ``i''
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local modcont `modcont' ``i''
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local ++nbpar
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}
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local modcont (`modcont'->T)
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}
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local modcat
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if "`categorical'"!="" {
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tokenize `categorical'
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local nbcat : word count `categorical'
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local categorical
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forvalues i=1/`nbcat' {
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local cat`i' ``i''
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local categorical `categorical' ``i''
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local modcat `modcat' i.``i''
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qui levelsof ``i''
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local levelsof``i'' `r(levels)'
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local nbpar=`nbpar'+`r(r)'-1
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*di "categorical : ``i'' levels : `levelsof``i'''"
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}
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local modcat (`modcat'->T)
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}
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if "`dirsave'"=="" {
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local dirsave `c(pwd)'
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}
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if "`genlt'"!=""|"`geninf'"!="" {
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capture confirm new variable `genlt' se`genlt' `geninf'
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if _rc!=0 {
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di in red "The variables `genlt', se`genlt' and/or `geninf' alreday exist. Please modify the -genlt- and/or -geninf- option"
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exit 198
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}
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}
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/*************************************************************************************************************
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GESTION DES ITEMS ET TESTS
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*************************************************************************************************************/
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tokenize `varlist'
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local nbitems : word count `varlist'
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marksample touse ,novarlist
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*preserve
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local modamax=1
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local modamin=0
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local pbmin
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local nbdiff=0
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forvalues i=1/`nbitems' {
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qui su ``i''
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if `r(min)'!=`modamin' {
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local modamin=r(min)
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local pbmin `pbmin' ``i''
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}
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if `r(max)'>`modamax' {
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local modamax=r(max)
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}
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local modamax``i''=r(max)
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if "`rsm'"=="" {
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local nbdiff=`nbdiff'+`modamax``i'''
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}
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}
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if "`rsm'"!="" {
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local nbdiff=`nbitems'+`modamax'-1
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}
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if `modamin'!=0 {
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di as error "The minimal answer category of each item must be coded by 0. This is not the case for the following items: `pbmin' (`modamin') "
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error 198
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}
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qui count
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local nbind=r(N)
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*set trace on
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local code
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forvalues k=1/`modamax' {
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local code`k'
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forvalues i=1/`nbitems' {
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if `k'<=`modamax``i''' {
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local code`k' `code`k'' `k'.``i''
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}
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}
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local code`k' (`code`k''<-T@`k')
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local code `code' `code`k''
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}
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/*************************************************************************************************************
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OPTION PCE
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*************************************************************************************************************/
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if "`pce'"!=""&"`difficulties'"=="" {
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tempname sedelta b
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qui raschpce `varlist'
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local ll=r(ll)
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matrix `sedelta'=r(sedelta)
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matrix `sedelta'=`sedelta''
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matrix `b'=r(b)
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*matrix `b'=`b''
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local difficulties `b'
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*matrix list `b'
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matrix loulou=`b'
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return matrix diff_parm=`b'
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`qui' pcm `varlist', diff(loulou) geninf(TInf_0) genlt(lt_0) /*postpce*/
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*exit
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}
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/*************************************************************************************************************
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RECUPERATION DES PARAMETRES DE DIFFICULTES ET DEFINITION DES CONTRAINTES
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*************************************************************************************************************/
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if "`difficulties'"!=""&"`rsm'"!="" {
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di as error "You can not defined in the same time the difficulties and the rsm options"
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error 198
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}
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if "`difficulties'"!="" {
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tempname beta
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matrix `beta'=J(`nbitems',`modamax',.)
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local t=1
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local constraints
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matrix list `difficulties'
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forvalues i=1/`nbitems' {
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forvalues k=1/`modamax``i''' {
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if `difficulties'[`i',`k']==. {
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di as error "The kth difficulty parameter of the item ``i'' is not correctly defined in the difficulties matrix"
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error 198
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}
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else {
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if `k'==1 {
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matrix `beta'[`i',1]=-`difficulties'[`i',1]
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}
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else {
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matrix `beta'[`i',`k']=`beta'[`i',`=`k'-1']-`difficulties'[`i',`k']
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}
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constraint `t' [`k'.``i'']_cons=`beta'[`i',`k']
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local constraints `constraints' `t'
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local ++t
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}
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}
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}
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}
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/*************************************************************************************************************
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DEFINITION DES CONTRAINTES POUR UN RSM
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*************************************************************************************************************/
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if "`rsm'"!="" {
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local t=1
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local constraints
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forvalues k=2/`modamax' {
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forvalues i=2/`nbitems' {
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constraint `t' [`=`k'-1'.``i'']_cons-[`k'.``i'']_cons+[1.``i'']_cons=[`=`k'-1'.`1']_cons-[`k'.`1']_cons+[1.`1']_cons
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local constraints `constraints' `t'
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local ++t
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}
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}
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}
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/*************************************************************************************************************
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MODELE
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*************************************************************************************************************/
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discard
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*di "`qui' gsem `code' `modcont' `modcat' ,iterate(`iterate') tol(`tolerance') constraint(`constraints')"
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local qui qui
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if "`model'"!="" {
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local qui
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}
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`qui' gsem `code' `modcont' `modcat' ,iterate(`iterate') tol(`tolerance') constraint(`constraints')
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local ll=e(ll)
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*set trace on
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tempvar latent score group selatent latent2
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tempname groups
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*capture qui predict mu, mu
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*su mu
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qui predict `latent',latent se(`selatent')
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if "`genlt'"!="" {
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gen `genlt'=`latent'
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gen se`genlt'=`selatent'
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}
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set seed 123456
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qui gen `latent2'=`latent'+invnorm(uniform())*`selatent'
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qui genscore `varlist',score(`score')
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qui gengroup `latent',newvariable(`group') continuous
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qui levelsof `group'
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local nbgroups=r(r)
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matrix `groups'=J(`nbgroups',`=`nbitems'+3',.)
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forvalues g=1/`nbgroups' {
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matrix `groups'[`g',`=`nbitems'+3']=0
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forvalues i=1/`nbitems' {
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*tab ``i'' if `group'==`g'
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qui count if ``i''!=.&`group'==`g'
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local n=r(N)
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if `n'>0 {
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qui su ``i'' if `group'==`g'
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matrix `groups'[`g',`i']=r(mean)
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matrix `groups'[`g',`=`nbitems'+3']=`groups'[`g',`=`nbitems'+3']+`r(mean)'
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}
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else {
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matrix `groups'[`g',`i']=.
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matrix `groups'[`g',`=`nbitems'+3']=.
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}
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}
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qui su `latent' if `group'==`g'
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matrix `groups'[`g',`=`nbitems'+1']=r(mean)
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qui count if `group'==`g'
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matrix `groups'[`g',`=`nbitems'+2']=r(N)
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}
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*matrix list `groups'
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qui count if `score'!=.
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local nbobsssmd=r(N)
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di
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di as text "Number of individuals:" %6.0f as result `nbobs'
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di as text "Number of complete individuals:" %6.0f as result `nbobsssmd'
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di as text "Number of items:" %6.0f as result `nbitems'
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di as text "Marginal log-likelihood:" %12.4f as result `ll'
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di
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return scalar ll=`ll'
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*set trace on
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/*************************************************************************************************************
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RECUPERATION DES ESTIMATIONS DES PARAMETRES DE DIFFICULTE
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*************************************************************************************************************/
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tempname diff diffmat vardiff diffmat2
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*set trace on
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qui matrix `diffmat'=J(`nbitems',`modamax',.)
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qui matrix `diffmat2'=J(`nbitems',`modamax',.)
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qui matrix `diff'=J(`nbdiff',6,.)
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local rn
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*qui matrix `vardiff'=J(`nbdiff',`nbdiff',.)
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*matrix list `diff'
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*set trace on
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local t=1
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forvalues i=1/`nbitems' {
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qui matrix `diffmat'[`i',1]=-_b[1.``i'':_cons]
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qui matrix `diffmat2'[`i',1]=-_b[1.``i'':_cons]
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qui lincom -_b[1.``i'':_cons]
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qui matrix `diff'[`t',1]=`r(estimate)'
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qui matrix `diff'[`t',2]=`r(se)'
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qui matrix `diff'[`t',3]=`r(z)'
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qui matrix `diff'[`t',4]=`r(p)'
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qui matrix `diff'[`t',5]=`r(lb)'
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qui matrix `diff'[`t',6]=`r(ub)'
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*qui matrix `vardiff'[`t',`t']=_se[1.``i'':_cons]^2
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local rn `rn' 1.``i''
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local ++t
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local sum _b[1.``i'':_cons]
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if "`rsm'"=="" {
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forvalues k=2/`modamax``i''' {
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local sum "_b[`k'.``i'':_cons]-(`sum')"
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di "``i'' `k' `sum'"
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local sum2 "_b[`=`k'-1'.``i'':_cons]-_b[`k'.``i'':_cons]"
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qui lincom (`sum2')
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*set trace on
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qui matrix `diffmat'[`i',`k']=`r(estimate)'
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qui matrix `diffmat2'[`i',`k']=`diffmat2'[`i',`=`k'-1']+`diffmat'[`i',`k']
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qui matrix `diff'[`t',1]=`r(estimate)'
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qui matrix `diff'[`t',2]=`r(se)'
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qui matrix `diff'[`t',3]=`r(z)'
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qui matrix `diff'[`t',4]=`r(p)'
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qui matrix `diff'[`t',5]=`r(lb)'
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qui matrix `diff'[`t',6]=`r(ub)'
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*qui matrix `vardiff'[`t',`t']=`r(se)'^2
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*set trace off
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local rn `rn' `k'.``i''
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local ++t
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}
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}
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}
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if "`rsm'"!="" {
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forvalues k=2/`modamax' {
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qui lincom _b[`=`k'-1'.`1':_cons]-_b[`k'.`1':_cons]+_b[1.`1':_cons]
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qui matrix `diff'[`t',1]=`r(estimate)'
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qui matrix `diff'[`t',2]=`r(se)'
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qui matrix `diff'[`t',3]=`r(z)'
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qui matrix `diff'[`t',4]=`r(p)'
|
||
|
|
qui matrix `diff'[`t',5]=`r(lb)'
|
||
|
|
qui matrix `diff'[`t',6]=`r(ub)'
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
qui matrix `diffmat'[`i',`k']=`diff'[`t',1]+`diffmat'[`i',1]
|
||
|
|
qui matrix `diffmat2'[`i',`k']=`diffmat'[`i',`k']+`diffmat2'[`i',`=`k'-1']
|
||
|
|
}
|
||
|
|
local rn `rn' tau`k'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local cn Estimate S.e. z p "Lower bound" "Upper Bound"
|
||
|
|
matrix colnames `diff'=`cn'
|
||
|
|
matrix rownames `diff'=`rn'
|
||
|
|
*matrix list `diff'
|
||
|
|
*matrix list `diffmat'
|
||
|
|
*matrix list `diffmat2'
|
||
|
|
*matrix list `vardiff'
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
RECUPERATION DES ESTIMATIONS DES PARAMETRES POUR LES COVARIABLES ET LA VARIANCE
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
tempname covariates
|
||
|
|
qui matrix `covariates'=J(`=`nbpar'+1',6,.)
|
||
|
|
|
||
|
|
*set trace on
|
||
|
|
if "`continuous'"!=""|"`categorical'"!="" {
|
||
|
|
qui lincom _b[/var(e.T)]
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
qui lincom _b[/var(T)]
|
||
|
|
}
|
||
|
|
qui matrix `covariates'[1,1]=`r(estimate)'
|
||
|
|
qui matrix `covariates'[1,2]=`r(se)'
|
||
|
|
qui matrix `covariates'[1,3]=`r(z)'
|
||
|
|
qui matrix `covariates'[1,4]=`r(p)'
|
||
|
|
qui matrix `covariates'[1,5]=`r(lb)'
|
||
|
|
qui matrix `covariates'[1,6]=`r(ub)'
|
||
|
|
|
||
|
|
local t=2
|
||
|
|
forvalues i=1/ `nbcont' {
|
||
|
|
qui lincom `cont`i''
|
||
|
|
qui matrix `covariates'[`t',1]=`r(estimate)'
|
||
|
|
qui matrix `covariates'[`t',2]=`r(se)'
|
||
|
|
qui matrix `covariates'[`t',3]=`r(z)'
|
||
|
|
qui matrix `covariates'[`t',4]=`r(p)'
|
||
|
|
qui matrix `covariates'[`t',5]=`r(lb)'
|
||
|
|
qui matrix `covariates'[`t',6]=`r(ub)'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
forvalues i=1/ `nbcat' {
|
||
|
|
local first=0
|
||
|
|
foreach j in `levelsof`cat`i''' {
|
||
|
|
if `first'==0 {
|
||
|
|
local ++first
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
qui lincom `j'.`cat`i''
|
||
|
|
qui matrix `covariates'[`t',1]=`r(estimate)'
|
||
|
|
qui matrix `covariates'[`t',2]=`r(se)'
|
||
|
|
qui matrix `covariates'[`t',3]=`r(z)'
|
||
|
|
qui matrix `covariates'[`t',4]=`r(p)'
|
||
|
|
qui matrix `covariates'[`t',5]=`r(lb)'
|
||
|
|
qui matrix `covariates'[`t',6]=`r(ub)'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
* matrix list `covariates'
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
OUTPUTS
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
if "`postpce'"=="" {
|
||
|
|
local t=1
|
||
|
|
local diffname
|
||
|
|
*set trace on
|
||
|
|
di "{hline 73}"
|
||
|
|
di as text _col(60) "<--95% IC -->"
|
||
|
|
di "Items" _col(60) "Lower" _col(68) "Upper"
|
||
|
|
di "parameters" _col(13) "category" _col(25) "Estimate" _col(37) "s.e." _col(48) "z" _col(56) "p" _col(59) " Bound" _col(68) "Bound"
|
||
|
|
di "{hline 73}"
|
||
|
|
*set trace on
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
*local l=1
|
||
|
|
forvalues j=1/`modamax``i''' {
|
||
|
|
if "`rsm'"==""|`j'==1 {
|
||
|
|
if `j'==1 {
|
||
|
|
di as text abbrev("``i''",19) _c
|
||
|
|
}
|
||
|
|
di as text _col(20) %5.2f "`j'" as result _col(28) %5.2f `diff'[`t',1] _col(36) %5.2f `diff'[`t',2] _col(44) %5.2f `diff'[`t',3] _col(52) %5.2f `diff'[`t',4] _col(60) %5.2f `diff'[`t',5] _col(68) %5.2f `diff'[`t',6]
|
||
|
|
local ++t
|
||
|
|
*local ++l
|
||
|
|
local diffname `diffname' `j'.``i''
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`rsm'"!="" {
|
||
|
|
forvalues k=2/`modamax' {
|
||
|
|
di as text "tau`k'" as result _col(28) %5.2f `diff'[`t',1] _col(36) %5.2f `diff'[`t',2] _col(44) %5.2f `diff'[`t',3] _col(52) %5.2f `diff'[`t',4] _col(60) %5.2f `diff'[`t',5] _col(68) %5.2f `diff'[`t',6]
|
||
|
|
local diffname `diffname' tau`k'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
}
|
||
|
|
di as text "{hline 73}"
|
||
|
|
local t=1
|
||
|
|
local n: word count Variance `continuous'
|
||
|
|
forvalues i=1/`n' {
|
||
|
|
local v: word `i' of Variance `continuous'
|
||
|
|
di as text _col(1) %5.2f "`v'" as result _col(28) %5.2f `covariates'[`t',1] _col(36) %5.2f `covariates'[`t',2] _col(44) %5.2f `covariates'[`t',3] _col(52) %5.2f `covariates'[`t',4] _col(60) %5.2f `covariates'[`t',5] _col(68) %5.2f `covariates'[`t',6]
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
|
||
|
|
local rn Variance `continuous'
|
||
|
|
|
||
|
|
local n: word count of `categorical'
|
||
|
|
local catname
|
||
|
|
forvalues i=1/`n' {
|
||
|
|
local v: word `i' of `categorical'
|
||
|
|
local first=1
|
||
|
|
local saute=1
|
||
|
|
foreach j in `levelsof`cat`i''' {
|
||
|
|
if `saute'==0 {
|
||
|
|
if `first'==1 {
|
||
|
|
di as text _col(1) abbrev("`v'",19) _c
|
||
|
|
}
|
||
|
|
di as text _col(20) %5.2f "`j'" as result _col(28) %5.2f `covariates'[`t',1] _col(36) %5.2f `covariates'[`t',2] _col(44) %5.2f `covariates'[`t',3] _col(52) %5.2f `covariates'[`t',4] _col(60) %5.2f `covariates'[`t',5] _col(68) %5.2f `covariates'[`t',6]
|
||
|
|
local ++first
|
||
|
|
local rn `rn' `j'.`n'
|
||
|
|
local ++t
|
||
|
|
local catname `catname' `j'.`v'
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local saute=0
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
di as text "{hline 73}"
|
||
|
|
di
|
||
|
|
qui su `latent'
|
||
|
|
qui local PSI=1-(`r(sd)')^2/((`covariates'[1,1])^2)
|
||
|
|
di as text "PSI:" as result %4.2f `PSI'
|
||
|
|
di
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
matrix colnames `covariates'=`cn'
|
||
|
|
matrix rownames `covariates'=`rn'
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
FIT TESTS
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
tempname fit
|
||
|
|
qui matrix `fit'=J(`nbitems',4,.)
|
||
|
|
matrix colnames `fit'=OUTFIT INFIT "Standardized OUTFIT" "Standardized INFIT"
|
||
|
|
matrix rownames `fit'=`varlist'
|
||
|
|
*matrix list `fit'
|
||
|
|
|
||
|
|
tempvar Tcum TInf cum
|
||
|
|
qui gen `Tcum'=0
|
||
|
|
qui gen `TInf'=0
|
||
|
|
if "`postpce'"=="" {
|
||
|
|
di as text "{hline 90}"
|
||
|
|
di as text _col(60) "<--- Standardized --->"
|
||
|
|
di as text "Items" _col(34) "OUTFIT" _col(50) "INFIT" _col(64) "OUTFIT" _col(80) "INFIT"
|
||
|
|
di as text "{hline 90}"
|
||
|
|
di as text "Referenced values*" _col(29) "[" %4.2f `=1-6/sqrt(`nbobs')' ";" %4.2f `=1+6/sqrt(`nbobs')' "]" _col(44) "[" %4.2f `=1-2/sqrt(`nbobs')' ";" %4.2f `=1+2/sqrt(`nbobs')' "]" _col(60) "[-2.6;2.6]" _col(75) "[-2.6;2.6]"
|
||
|
|
di as text "Referenced values**" _col(29) "[0.75;1.30]" _col(44) "[0.75;1.30]" _col(60) "[-2.6;2.6]" _col(75) "[-2.6;2.6]"
|
||
|
|
di as text "{hline 90}"
|
||
|
|
}
|
||
|
|
*set trace on
|
||
|
|
local chi2=0
|
||
|
|
local chi2_old=0
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
local chi2_g`g'=0
|
||
|
|
local chi2_old_g`g'=0
|
||
|
|
}
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
if "`rsm'"=="" {
|
||
|
|
local mm=`modamax``i'''
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local mm `modamax'
|
||
|
|
}
|
||
|
|
tempvar cum_old``i'' c_old0_``i'' Inf_old``i'' y_old``i'' y2_old``i''
|
||
|
|
tempvar cum``i'' c0_``i'' Inf``i'' C``i'' C2``i'' C3``i'' y``i'' y2``i'' z``i'' z2``i'' i``i''
|
||
|
|
|
||
|
|
local d=1
|
||
|
|
local d_old=1
|
||
|
|
qui gen `cum``i'''=0
|
||
|
|
qui gen `cum_old``i'''=0
|
||
|
|
forvalues k=1/`mm' {
|
||
|
|
local d `d'+exp(`k'*`latent2'-`diffmat2'[`i',`k'])
|
||
|
|
local d_old `d_old'+exp(`k'*`latent'-`diffmat2'[`i',`k'])
|
||
|
|
}
|
||
|
|
qui gen `c0_``i'''=1/(`d')
|
||
|
|
qui gen `c_old0_``i'''=1/(`d_old')
|
||
|
|
forvalues k=1/`mm' {
|
||
|
|
tempvar c`k'_``i'' c_old`k'_``i''
|
||
|
|
qui gen `c`k'_``i'''=exp(`k'*`latent2'-`diffmat2'[`i',`k'])/(`d')
|
||
|
|
qui gen `c_old`k'_``i'''=exp(`k'*`latent'-`diffmat2'[`i',`k'])/(`d')
|
||
|
|
qui replace `cum``i'''=`cum``i'''+`c`k'_``i'''*`k'
|
||
|
|
qui replace `cum_old``i'''=`cum_old``i'''+`c_old`k'_``i'''*`k'
|
||
|
|
}
|
||
|
|
qui gen `Inf``i'''=0
|
||
|
|
qui gen `Inf_old``i'''=0
|
||
|
|
qui gen `C``i'''=0
|
||
|
|
forvalues k=0/`mm' {
|
||
|
|
qui replace `Inf``i'''=`Inf``i'''+(`k'-`cum``i''')^2*`c`k'_``i'''
|
||
|
|
qui replace `Inf_old``i'''=`Inf_old``i'''+(`k'-`cum_old``i''')^2*`c_old`k'_``i'''
|
||
|
|
qui replace `C``i'''=`C``i'''+(`k'-`cum``i''')^4*`c`k'_``i'''
|
||
|
|
}
|
||
|
|
qui count if ``i''!=.
|
||
|
|
local n``i''=r(N)
|
||
|
|
|
||
|
|
qui gen `C2``i'''=`C``i'''/((`Inf``i''')^2)
|
||
|
|
qui su `C2``i'''
|
||
|
|
local q2o``i''=(`r(mean)'-1)/((`n``i'''))
|
||
|
|
|
||
|
|
qui gen `C3``i'''=`C``i'''-(`Inf``i''')^2
|
||
|
|
qui su `C3``i'''
|
||
|
|
local n=r(sum)
|
||
|
|
qui su `Inf``i'''
|
||
|
|
local d=r(sum)
|
||
|
|
local q2i``i''=`n'/((`d')^2)
|
||
|
|
|
||
|
|
//di "``i'' qo = `=sqrt(`q2o``i''')' qi = `=sqrt(`q2i``i''')'"
|
||
|
|
|
||
|
|
qui replace `Tcum'=`Tcum'+`cum``i'''
|
||
|
|
qui replace `TInf'=`TInf'+`Inf``i'''
|
||
|
|
qui gen `y``i'''=``i''-`cum``i'''
|
||
|
|
qui gen `y_old``i'''=``i''-`cum_old``i'''
|
||
|
|
qui gen `y2``i'''=(`y``i''')^2
|
||
|
|
qui gen `y2_old``i'''=(`y_old``i''')^2
|
||
|
|
qui gen `z``i'''=(`y``i'''/sqrt(`Inf``i'''))
|
||
|
|
local chi2_``i''=0
|
||
|
|
local chi2_old_``i''=0
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
qui su `y2``i''' if `group'==`g'
|
||
|
|
local n=r(sum)
|
||
|
|
qui su ``i'' if `group'==`g'
|
||
|
|
local n1=r(sum)
|
||
|
|
qui su `cum``i''' if `group'==`g'
|
||
|
|
local n2=r(sum)
|
||
|
|
qui su `Inf``i''' if `group'==`g'
|
||
|
|
local d=r(sum)
|
||
|
|
*di "chi2_`g'_``i''=`chi2'+(`n1'-`n2')^2/(`d')"
|
||
|
|
local chi2=`chi2'+(`n1'-`n2')^2/(`d')
|
||
|
|
local chi2_``i''=`chi2_``i'''+(`n1'-`n2')^2/(`d')
|
||
|
|
local chi2_g`g'=`chi2_g`g''+(`n1'-`n2')^2/(`d')
|
||
|
|
qui su `y2_old``i''' if `group'==`g'
|
||
|
|
local n_old=r(sum)
|
||
|
|
qui su ``i'' if `group'==`g'
|
||
|
|
local n1_old=r(sum)
|
||
|
|
qui su `cum_old``i''' if `group'==`g'
|
||
|
|
local n2_old=r(sum)
|
||
|
|
qui su `Inf_old``i''' if `group'==`g'
|
||
|
|
local d_old=r(sum)
|
||
|
|
local chi2_old=`chi2_old'+(`n1_old'-`n2_old')^2/(`d_old')
|
||
|
|
local chi2_old_``i''=`chi2_old_``i'''+(`n_old')/(`d_old')
|
||
|
|
local chi2_old_g`g'=`chi2_old_g`g''+(`n_old')/(`d_old')
|
||
|
|
}
|
||
|
|
*di "Item ``i'' Chi2``i''=`chi2_``i''' et chi2=`chi2' Chi2_old=`chi2_old_``i''' et chi2_old=`chi2_old' "
|
||
|
|
*su `z``i'''
|
||
|
|
label variable `z``i''' "Standardized residuals associated to ``i''"
|
||
|
|
label variable `latent' "Latent trait"
|
||
|
|
*set trace on
|
||
|
|
if "`graphs'"!=""&"`graphitems'"=="" {
|
||
|
|
if "`filesave'"!="" {
|
||
|
|
local fs saving("`dirsave'//residuals_``i''",replace)
|
||
|
|
}
|
||
|
|
qui graph twoway scatter `z``i''' `latent', name(residuals``i'',replace) title("Standardized residuals associated to ``i''") `fs'
|
||
|
|
}
|
||
|
|
*set trace off
|
||
|
|
qui gen `z2``i'''=(`z``i''')^2
|
||
|
|
qui su `z2``i'''
|
||
|
|
local OUTFIT``i''=`r(mean)'
|
||
|
|
qui matrix `fit'[`i',1]=`OUTFIT``i'''
|
||
|
|
local OUTFITs``i''=((`r(mean)')^(1/3)-1)*(3/sqrt(`q2o``i'''))+sqrt(`q2o``i''')/3
|
||
|
|
qui matrix `fit'[`i',3]=`OUTFITs``i'''
|
||
|
|
qui su `Inf``i''' if ``i''!=.
|
||
|
|
local sumw``i''=r(sum)
|
||
|
|
qui gen `i``i'''=`Inf``i'''*`z2``i'''
|
||
|
|
qui su `i``i''' if ``i''!=.
|
||
|
|
local INFIT``i'' = `=`r(sum)'/`sumw``i''''
|
||
|
|
qui matrix `fit'[`i',2]=`INFIT``i'''
|
||
|
|
local INFITs``i''=(`=`r(sum)'/`sumw``i''''^(1/3)-1)*(3/sqrt(`q2i``i'''))+sqrt(`q2i``i''')/3
|
||
|
|
qui matrix `fit'[`i',4]=`INFITs``i'''
|
||
|
|
if "`postpce'"=="" {
|
||
|
|
di abbrev("``i''",19) _col(35) %5.3f `OUTFIT``i''' _col(50) %5.3f `INFIT``i''' _col(64) %6.3f `OUTFITs``i''' _col(79) %6.3f `INFITs``i'''
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`postpce'"=="" {
|
||
|
|
di as text "{hline 90}"
|
||
|
|
di as text "*: As suggested by Wright (Smith, 1998)
|
||
|
|
di as text "**: As suggested by Bond and Fox (2007)
|
||
|
|
}
|
||
|
|
if "`geninf'"!="" {
|
||
|
|
gen `geninf'=`TInf'
|
||
|
|
}
|
||
|
|
|
||
|
|
*set trace off
|
||
|
|
/*************************************************************************************************************
|
||
|
|
ESTIMATION OF THE WEIGHTED ML ESTIMATORS
|
||
|
|
**************************************************************************************************************/
|
||
|
|
*set trace on
|
||
|
|
*di "estimation `wmliterate'"
|
||
|
|
if "`postpce'"!="" {
|
||
|
|
local conv=10
|
||
|
|
local it=`wmliterate'
|
||
|
|
di "Iteration : `it'"
|
||
|
|
while(`conv'>=1) {
|
||
|
|
di "Itération `it' : conv=`conv'"
|
||
|
|
tempvar sinf
|
||
|
|
qui gen `sinf'=sqrt(TInf_`=`it'-1')
|
||
|
|
`qui' pcm `varlist' [iweight=`sinf'],diff(loulou) wmliterate(`it') geninf(TInf_`it') genlt(lt_`it')
|
||
|
|
tempvar ecart_`it'
|
||
|
|
qui gen `ecart_`it''=abs(lt_`it'-lt_`=`it'-1')
|
||
|
|
qui su `ecart_`it''
|
||
|
|
local conv =r(mean)
|
||
|
|
local ++it
|
||
|
|
}
|
||
|
|
exit
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
Categories/Items/Test Characteristics Curves and Information graphs
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
if "`graphs'"!="" {
|
||
|
|
|
||
|
|
tempfile savefile
|
||
|
|
qui save `savefile'
|
||
|
|
|
||
|
|
qui clear
|
||
|
|
qui set obs 2000
|
||
|
|
qui gen u=(_n-1000)/250
|
||
|
|
qui gen Tcum=0
|
||
|
|
qui gen TInf=0
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local scatteri`i'
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
local x=`groups'[`g',`=`nbitems'+1']
|
||
|
|
local y=`groups'[`g',`i']
|
||
|
|
local s1=`groups'[`g',`=`nbitems'+2']
|
||
|
|
local seuil=30
|
||
|
|
local s vtiny
|
||
|
|
*set trace on
|
||
|
|
foreach lab in tiny vsmall small medsmall medium medlarge large vlarge huge vhuge /*ehuge*/ {
|
||
|
|
if `s1'>`seuil' {
|
||
|
|
local s `lab'
|
||
|
|
}
|
||
|
|
local seuil=`seuil'+10
|
||
|
|
}
|
||
|
|
local scatteri`i' `scatteri`i'' || scatteri `y' `x' , mcolor(black) msize(`s') legend(off)
|
||
|
|
*set trace off
|
||
|
|
}
|
||
|
|
local d=1
|
||
|
|
qui gen cum``i''=0
|
||
|
|
*set trace on
|
||
|
|
if "`rsm'"=="" {
|
||
|
|
local mm=`modamax``i'''
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local mm `modamax'
|
||
|
|
}
|
||
|
|
forvalues k=1/`mm' {
|
||
|
|
local d `d'+exp(`k'*u-`diffmat2'[`i',`k'])
|
||
|
|
}
|
||
|
|
qui gen c0_``i''=1/(`d')
|
||
|
|
label variable c0_``i'' "Pr(``i''=0)"
|
||
|
|
forvalues k=1/`mm' {
|
||
|
|
qui gen c`k'_``i''=exp(`k'*u-`diffmat2'[`i',`k'])/(`d')
|
||
|
|
qui replace cum``i''=cum``i''+c`k'_``i''*`k'
|
||
|
|
label variable c`k'_``i'' "Pr(``i''=`k')"
|
||
|
|
}
|
||
|
|
qui gen Inf``i''=0
|
||
|
|
forvalues k=1/`mm' {
|
||
|
|
qui replace Inf``i''=Inf``i''+(`k'-cum``i'')^2*c`k'_``i''
|
||
|
|
}
|
||
|
|
if "`graphitems'"=="" {
|
||
|
|
if "`filesave'"!="" {
|
||
|
|
local fsc saving("`dirsave'//CCC_``i''",replace)
|
||
|
|
local fsi saving("`dirsave'//ICC_``i''",replace)
|
||
|
|
}
|
||
|
|
qui graph twoway line c*_``i'' u , name(CCC``i'', replace) title(Categories Characteristic Curve (CCC) of ``i'') ytitle("Probability") xtitle("Latent trait") `fsc'
|
||
|
|
qui graph twoway line cum``i'' u, name(ICC``i'',replace) title("Item Characteristic Curve (ICC) of ``i''") ytitle("Score to the item") xtitle("Latent trait") `scatteri`i'' `fsi'
|
||
|
|
}
|
||
|
|
qui replace Tcum=Tcum+cum``i''
|
||
|
|
qui replace TInf=TInf+Inf``i''
|
||
|
|
label variable Inf``i'' "``i''"
|
||
|
|
}
|
||
|
|
if "`filesave'"!="" {
|
||
|
|
local fst saving("`dirsave'//TCC",replace)
|
||
|
|
local fsteo saving("`dirsave'//TCCeo",replace)
|
||
|
|
local fsi saving("`dirsave'//ICC",replace)
|
||
|
|
local fsti saving("`dirsave'//TIC",replace)
|
||
|
|
local fsm saving("`dirsave'//map",replace)
|
||
|
|
}
|
||
|
|
qui graph twoway line Tcum u, name(TCC,replace) title("Test Characteristic Curve (TCC)") ytitle("Score to the test") xtitle("Latent trait") `fst'
|
||
|
|
qui graph twoway line Inf* u, name(IIC,replace) title("Item Information Curves") ytitle("Information") xtitle("Latent trait") `fsi'
|
||
|
|
qui graph twoway line TInf u, name(TIC,replace) title("Test Information Curve") ytitle("Information") xtitle("Latent trait") `fsti'
|
||
|
|
|
||
|
|
local scatteri
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
local x=`groups'[`g',`=`nbitems'+1']
|
||
|
|
local y=`groups'[`g',`=`nbitems'+3']
|
||
|
|
local s1=`groups'[`g',`=`nbitems'+2']
|
||
|
|
local seuil=30
|
||
|
|
local s vtiny
|
||
|
|
*set trace on
|
||
|
|
foreach lab in tiny vsmall small medsmall medium medlarge large vlarge huge vhuge /*ehuge*/ {
|
||
|
|
if `s1'>`seuil' {
|
||
|
|
local s `lab'
|
||
|
|
}
|
||
|
|
local seuil=`seuil'+10
|
||
|
|
}
|
||
|
|
local scatteri `scatteri' || scatteri `y' `x' , mcolor(black) msize(`s') legend(off)
|
||
|
|
}
|
||
|
|
qui graph twoway line Tcum u , name(TCCeo,replace) title("Test Characteristic Curve (TCC)") ytitle("Score to the test") xtitle("Latent trait") `scatteri' `fsteo'
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
MAP
|
||
|
|
*************************************************************************************************************/
|
||
|
|
*set trace on
|
||
|
|
gen eff=0
|
||
|
|
local effmax=0
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
local eff=`groups'[`g',`=`nbitems'+2']
|
||
|
|
if `groups'[`g',`=`nbitems'+2']>`effmax' {
|
||
|
|
local effmax=`groups'[`g',`=`nbitems'+2']
|
||
|
|
}
|
||
|
|
local lat=round(`groups'[`g',`=`nbitems'+1'],0.004)
|
||
|
|
*di "replace eff=`eff' if round(u,0.004)==`lat'"
|
||
|
|
qui replace eff=`eff' if round(u,0.004)==`lat'
|
||
|
|
}
|
||
|
|
gen density=normalden(u)*sqrt(`covariates'[1,1])
|
||
|
|
label variable eff "Frequencies"
|
||
|
|
label variable u "Latent trait"
|
||
|
|
label variable TInf "Information curve"
|
||
|
|
label variable density "Density function of the latent trait"
|
||
|
|
local scatteri
|
||
|
|
qui su u if eff!=0
|
||
|
|
*set trace on
|
||
|
|
local floor=floor(`r(min)')
|
||
|
|
local ceil=ceil(`r(max)')
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local color`i':word `i' of `color'
|
||
|
|
local y=-`i'*`effmax'/`nbitems'
|
||
|
|
forvalues l=1/`modamax' {
|
||
|
|
local x=`diffmat'[`i',`l']
|
||
|
|
local scatteri `scatteri' || scatteri `y' `x' "`l'" ,mcolor(black) mlabcolor(black)
|
||
|
|
if `x'<`floor' {
|
||
|
|
local floor=floor(`x')
|
||
|
|
}
|
||
|
|
if `x'>`ceil'&`x'!=. {
|
||
|
|
local ceil=ceil(`x')
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local scatteri `scatteri' || scatteri `y' `floor' "``i''",mcolor(black) mlabcolor(black) msize(vtiny)
|
||
|
|
}
|
||
|
|
qui su eff
|
||
|
|
local maxe=ceil(`=(floor(`r(max)'/10)+1)*10')
|
||
|
|
qui su TInf
|
||
|
|
local maxi=ceil(`r(max)')
|
||
|
|
qui su density
|
||
|
|
local maxd=ceil(`r(max)')
|
||
|
|
qui drop if u<`floor'|u>`ceil'
|
||
|
|
qui graph twoway (bar eff u, barwidth(.2) yaxis(1) legend(off) xlabel(`floor'(1)`ceil')) (line TInf u,yaxis(2)) (line density u,yaxis(3)) `scatteri' , name(map,replace) ytitle("Frequencies") ylabel(-`maxi'(`=`maxi'/5')`maxi' ,axis(2)) ylabel(-`maxd'(`=`maxd'/5')`maxd' ,axis(3)) ylabel(-`maxe'(`=`maxe'/5')`maxe' ,axis(1)) title("Individuals/items representations (Map)") xsize(12) ysize(9) note("Red line: Information curve - Green line : Density of the latent trait") xtitle("Latent trait") `fsm'
|
||
|
|
|
||
|
|
|
||
|
|
qui clear
|
||
|
|
qui use `savefile'
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
RESULTS BY GROUP
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
di
|
||
|
|
di as text "{hline 57}"
|
||
|
|
di _col(31) "Latent Variable" _col(50) "Expected"
|
||
|
|
di "Group" _col(10) "Score" _col(20) "Freq" _col(32) "Mean" _col(42) "s.e." _col(53) "Score"
|
||
|
|
di as text "{hline 57}"
|
||
|
|
*set trace on
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
qui count if `group'==`g'
|
||
|
|
local eff`g'=r(N)
|
||
|
|
qui count if `score'!=.&`group'==`g'
|
||
|
|
local n=r(N)
|
||
|
|
di as text "`g' (n=" as result `eff`g'' as text ")" _c
|
||
|
|
if `n'>0 {
|
||
|
|
qui su `score' if `group'==`g'
|
||
|
|
local scoremin`g'=`r(min)'
|
||
|
|
local scoremax`g'=`r(max)'
|
||
|
|
forvalues s=`scoremin`g''/`scoremax`g'' {
|
||
|
|
qui count if `group'==`g'&`score'==`s'
|
||
|
|
local eff=r(N)
|
||
|
|
qui su `latent' if `group'==`g'&`score'==`s'
|
||
|
|
local mean=r(mean)
|
||
|
|
qui su `selatent' if `group'==`g'&`score'==`s'
|
||
|
|
local se=r(mean)
|
||
|
|
qui su `Tcum' if `group'==`g'&`score'==`s'
|
||
|
|
local exp=r(mean)
|
||
|
|
if `eff'>0 {
|
||
|
|
di as text _col(10) %5.0f `s' as result _col(20) %4.0f `eff' _col(30) %6.3f `mean' _col(40) %6.3f `se' _col(53) %5.2f `exp'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
qui count if `group'==`g'&`score'==.
|
||
|
|
local eff=r(N)
|
||
|
|
qui su `latent' if `group'==`g'&`score'==.
|
||
|
|
local mean=r(mean)
|
||
|
|
qui su `selatent' if `group'==`g'&`score'==.
|
||
|
|
local se=r(mean)
|
||
|
|
qui su `Tcum' if `group'==`g'&`score'==.
|
||
|
|
local exp=r(mean)
|
||
|
|
if `eff'>0 {
|
||
|
|
di as text _col(10) " ." as result _col(20) %4.0f `eff' _col(30) %6.3f `mean' _col(40) %6.3f `se' _col(53) %5.2f `exp'
|
||
|
|
}
|
||
|
|
di as text "{hline 57}"
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
CREATION DU DOCX
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
if "`docx'"!="" {
|
||
|
|
putdocx clear
|
||
|
|
putdocx begin
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("General informations") , bold underline font(,14) smallcaps
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Number of individuals: `nbobs'")
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Number of complete individuals: `nbobsssmd'")
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Number of items: `nbitems'")
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("List of items: `varlist'")
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Date: $S_DATE, $S_TIME")
|
||
|
|
putdocx paragraph
|
||
|
|
local model Partial Credit Model (PCM)
|
||
|
|
if "`rsm'"!="" {
|
||
|
|
local model Rating Scale Model (RSM)
|
||
|
|
}
|
||
|
|
putdocx text ("Model: `model'")
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Marginal log-likelihood: `ll'")
|
||
|
|
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Estimation of the parameters") , bold underline font(,14) smallcaps
|
||
|
|
putdocx table tablename = matrix(`diff') , nformat(%9.3f) rownames colnames border(start, nil) border(insideH, nil) border(insideV, nil) border(end, nil)
|
||
|
|
qui putdocx table tablename = matrix(`covariates') , nformat(%9.3f) rownames colnames border(start, nil) border(insideH, nil) border(insideV, nil) border(end, nil)
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Fit indexes for items") , bold underline font(,14) smallcaps
|
||
|
|
qui putdocx table tablename = matrix(`fit') , nformat(%9.3f) rownames colnames border(start, nil) border(insideH, nil) border(insideV, nil) border(end, nil)
|
||
|
|
local extension png
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
SAUVEGARDE DES GRAPHIQUES
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
*set trace on
|
||
|
|
if "`filesave'"!="" {
|
||
|
|
if "`graphs'"!="" {
|
||
|
|
if "`docx'"!="" {
|
||
|
|
putdocx pagebreak
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("General graphs") , bold underline font(,14) smallcaps
|
||
|
|
}
|
||
|
|
foreach i in TCC TCCeo TIC IIC map {
|
||
|
|
if "`extension'"!="" {
|
||
|
|
qui graph export "`dirsave'//`i'.`extension'", replace name(`i')
|
||
|
|
}
|
||
|
|
*graph display `i'
|
||
|
|
*qui graph save "`dirsave'//`i'", replace
|
||
|
|
if "`docx'"!="" {
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx image "`dirsave'//`i'.png", height(10cm)
|
||
|
|
}
|
||
|
|
}
|
||
|
|
*discard
|
||
|
|
if "`graphitems'"=="" {
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
if "`docx'"!="" {
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx text ("Graphs for ``i''") , bold underline font(,14) smallcaps
|
||
|
|
}
|
||
|
|
foreach j in CCC ICC residuals {
|
||
|
|
*graph display `j'``i''
|
||
|
|
*qui graph save "`dirsave'//`j'_``i''", replace
|
||
|
|
|
||
|
|
if "`extension'"!="" {
|
||
|
|
qui graph export "`dirsave'//`j'_``i''.`extension'", replace name(`j'``i'')
|
||
|
|
}
|
||
|
|
if "`docx'"!="" {
|
||
|
|
putdocx paragraph
|
||
|
|
putdocx image "`dirsave'//`j'_``i''.png" , height(10cm)
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`docx'"!="" {
|
||
|
|
putdocx save "`dirsave'//`docx'.docx", replace
|
||
|
|
}
|
||
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/*************************************************************************************************************
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RETURNS
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*************************************************************************************************************/
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matrix colnames `diff'=Estimate "s.e." z p lb ul
|
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matrix colnames `covariates'=Estimate "s.e." z p lb ul
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matrix rownames `diff'=`diffname'
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matrix rownames `covariates'=Variance `continuous' `catname'
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return matrix difficulties=`diff'
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||
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return matrix covariates=`covariates'
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|
capture restore, not
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||
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|
end
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