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1772 lines
60 KiB
Plaintext
1772 lines
60 KiB
Plaintext
8 months ago
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*! Version 5 2August2022
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*! Jean-Benoit Hardouin, Myriam Blanchin
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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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* Version 3.5 : August 29th, 2019 [Jean-Benoit Hardouin] : Correction of a bug with modamax``i''
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* Version 4: September 13th, 2019 [Myriam Blanchin]: addition of longitudinal pcm
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* Version 4.1: September 15th, 2019 [Jean-Benoit Hardouin]: correction of a small bug in the outputs
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* Version 4.2: September 27th, 2019 [Jean-Benoit Hardouin] : EQUATING
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* Version 4.3: November 8th, 2019 [Jean-Benoit Hardouin] : add a constant when difficulty parameters are fixed
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* Version 5: August 2nd, 2022 [Jean-Benoit Hardouin] : New MAP graph, corrected estimation of the latent trait
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*
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*
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* Jean-benoit Hardouin, Myriam Blanchin - 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, myriam.blanchin@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, 2022 Jean-Benoit Hardouin, Myriam Blanchin
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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) VARiance(real -1) rsm Graphs noGRAPHItems filesave dirsave(string) docx(string) extension(string) PCE WMLiterate(int 1) GENLT(string) GENINF(string) REPlace postpce visit(varname) id(varname) eqset1(varlist) eqset2(varlist) EQGraph minsize(int 30)]
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preserve
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/*************************************************************************************************************
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QUELQUES TESTS
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*************************************************************************************************************/
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if `variance'!=-1&`variance'<=0 {
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di in red "The -variance- option cannot be negative"
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exit 198
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}
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if `variance'!=-1&"`visit'"!="" {
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di in red "The -variance- and -visit- options cannot be used simultaneously."*
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exit 198
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}
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if "`genlt'"!=""|"`geninf'"!="" {
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capture confirm new variable `genlt' `genlt'_se `geninf' `genlt'_corr `genlt'_opt `genlt'_opt_se
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if _rc!=0&"`replace'"=="" {
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di in red "The variables `genlt', `genlt'_se, `genlt'_corr, `genlt'_opt, `genlt'_opt_se 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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if _rc!=0&"`replace'"!="" {
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qui capture drop `genlt'
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qui capture drop `genlt'_se
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qui capture drop `geninf'
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qui capture drop `genlt'_corr
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qui capture drop `genlt'_opt
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qui capture drop `genlt'_opt_se
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}
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}
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if ("`eqset1'"!=""&"`eqset2'"=="")|("`eqset1'"==""&"`eqset2'"!="") {
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di in red "The two options -eqset1- and -eqset2- must be used simultaneously"
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exit 198
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}
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if ("`eqset1'"!=""&"`graphs'"!="") {
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di in red "The two options -eqset1- and -graph- cannot be used simultaneously"
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exit 198
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}
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/*************************************************************************************************************
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GESTION DES VARIABLES CONTINUES ET CATEGORIELLES
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*************************************************************************************************************/
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if "`visit'"!=""{
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if "`id'"==""{
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di in red "Option -visit- must be combined with option -id-. Please fill in the -id- option"
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exit 198
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}
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qui levelsof `visit'
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local levelsofv `r(levels)'
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local nbvisits=r(r)
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local timemin: word 1 of `levelsofv'
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local timemax: word `nbvisits' of `levelsofv'
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if `timemax'>5{
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di as error "You must use a discrete time variable (-visit- option) with less than 5 measurement occasions"
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error 198
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}
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if `timemin'!=1{
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di as error "You must use a -visit- variable coded at 1 for the first visit"
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error 198
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}
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qui reshape wide `varlist', i(`id') j(`visit')
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local multivist=1
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}
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else {
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local timemax=1
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foreach i in `varlist' {
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*rename `i' `i'1
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}
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local multivisit
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}
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qui count
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local nbobs=r(N)
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local timelist
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forvalues t=1/`timemax'{
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local timelist `timelist' T`t'
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}
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local modcont
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local premodcont
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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 premodcont (`modcont'->T1)
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local modcont (`modcont'->`timelist')
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}
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local modcat
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local premodcat
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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 premodcat (`modcat'->T1)
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local modcat (`modcat'->`timelist')
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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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/*************************************************************************************************************
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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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local scoremax=0
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forvalues i=1/`nbitems' {
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local modamax`i'=1
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local modamax``i''=1
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if `timemax'>1 {
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forvalues t=1/`timemax'{
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*qui replace ``i'`t''=``i'`t''-`min'
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qui su ``i''`t'
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if `r(min)'!=`modamin' {
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local modamin=r(min)
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local pbmin `pbmin' ``i'`t''
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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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if `r(max)'>`modamax`i'' {
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local modamax`i'=r(max)
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}
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}
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}
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else {
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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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if `r(max)'>`modamax`i'' {
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local modamax`i'=r(max)
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local modamax``i''=r(max)
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}
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}
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*di "local scoremax=`scoremax'+`modamax`i''"
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local scoremax=`scoremax'+`modamax`i''
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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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local precode
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if `timemax'>1 {
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forvalues k=1/`modamax' {
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forvalues t=1/`timemax'{
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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''`t'
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}
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}
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local code`k' (`code`k''<-T`t'@`k')
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if `t'==1{
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local precode `precode' `code`k''
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}
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local code `code' `code`k''
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}
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}
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}
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else {
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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''<-T1@`k')
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local precode `precode' `code`k''
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local code `code' `code`k''
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}
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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'"==""&"`visit'"=="" {
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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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local t=1
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local constraints
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local codemean
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local codevar
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local codecov
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forvalues j=2/`timemax'{
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forvalues i=1/`nbitems' {
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forvalues k=1/`modamax`i'' {
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qui constraint `t' [`k'.``i''`j']_cons=[`k'.``i''`multivisit']_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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if "`continuous'"=="" & "`categorical'"==""{
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local codemean `codemean' T`j'@m`j'
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local codevar `codevar' T`j'@v`j'
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forvalues l=1/`=`j'-1'{
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local codecov `codecov' T`l'*T`j'@cov`l'`j'
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}
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}
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else{
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local codevar `codevar' e.T`j'@v`j'
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forvalues l=1/`=`j'-1'{
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local codecov `codecov' e.T`l'*e.T`j'@cov`l'`j'
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}
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}
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}
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if `timemax'>1{
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if "`continuous'"=="" & "`categorical'"==""{
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local codelg means(T1@0 `codemean') var(T1@v1 `codevar') cov(`codecov')
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}
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else{
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local codelg var(e.T1@v1 `codevar') cov(`codecov')
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}
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}
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else {
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local constrvar
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if `variance'>0 {
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if "`continuous'"=="" & "`categorical'"==""{
|
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local constrvar var(T1@`variance')
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}
|
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else{
|
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*local constrvar var(e.T1@`variance')
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}
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}
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}
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local fixedmean
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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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matrix list `difficulties'
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
forvalues k=1/`modamax`i'' {
|
||
|
|
if `difficulties'[`i',`k']==. {
|
||
|
|
di as error "The kth difficulty parameter of the item ``i'' is not correctly defined in the difficulties matrix"
|
||
|
|
error 198
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
if `k'==1 {
|
||
|
|
matrix `beta'[`i',1]=-`difficulties'[`i',1]
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
matrix `beta'[`i',`k']=`beta'[`i',`=`k'-1']-`difficulties'[`i',`k']
|
||
|
|
}
|
||
|
|
qui constraint `t' [`k'.``i''`multivisit']_cons=`beta'[`i',`k']
|
||
|
|
local constraints `constraints' `t'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`continuous'"=="" & "`categorical'"=="" {
|
||
|
|
local fixedmean mean(T1)
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
local fixedmean
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
DEFINITION DES CONTRAINTES POUR UN RSM
|
||
|
|
*************************************************************************************************************/
|
||
|
|
if "`rsm'"!="" {
|
||
|
|
local constraints
|
||
|
|
forvalues k=2/`modamax' {
|
||
|
|
forvalues i=2/`nbitems' {
|
||
|
|
qui constraint `t' [`=`k'-1'.``i''`multivisit']_cons-[`k'.``i''`multivisit']_cons+[1.``i''`multivisit']_cons=[`=`k'-1'.`1'1]_cons-[`k'.`1'1]_cons+[1.`1'1]_cons
|
||
|
|
local constraints `constraints' `t'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
MODELE
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
|
||
|
|
discard
|
||
|
|
*di "`qui' gsem `code' `modcont' `modcat' ,iterate(`iterate') tol(`tolerance') constraint(`constraints') latent(`timelist') `codelg' "
|
||
|
|
if "`model'"!="" {
|
||
|
|
local qui
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local qui qui
|
||
|
|
}
|
||
|
|
if `timemax'==1{
|
||
|
|
di "`qui' gsem `code' `modcont' `modcat' ,iterate(`iterate') tol(`tolerance') constraint(`constraints') latent(`timelist') `constrvar' `fixedmean'"
|
||
|
|
`qui' gsem `code' `modcont' `modcat' ,iterate(`iterate') tol(`tolerance') constraint(`constraints') latent(`timelist') `constrvar' `fixedmean'
|
||
|
|
*qui gen un=1
|
||
|
|
*`qui' gsem `code' (i.group un->T) ,iterate(`iterate') tol(`tolerance') constraint(`constraints') latent(`timelist') `constrvar' `fixedmean'
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
di "`qui' gsem `precode' `premodcont' `premodcat',iterate(`iterate') tol(`tolerance') "
|
||
|
|
`qui' gsem `precode' `premodcont' `premodcat',iterate(`iterate') tol(`tolerance') constraint(`constraints')
|
||
|
|
matrix esti_B = e(b)
|
||
|
|
di "`qui' gsem `code' `modcont' `modcat' ,iterate(`iterate') tol(`tolerance') constraint(`constraints') latent(`timelist') `codelg' from(esti_B,skip)"
|
||
|
|
`qui' gsem `code' `modcont' `modcat' ,iterate(`iterate') tol(`tolerance') constraint(`constraints') latent(`timelist') `codelg' from(esti_B,skip)
|
||
|
|
}
|
||
|
|
local ll=e(ll)
|
||
|
|
|
||
|
|
*set trace on
|
||
|
|
tempvar latent score group selatent latent2 miss
|
||
|
|
tempname groups
|
||
|
|
*capture qui predict mu, mu
|
||
|
|
*su mu
|
||
|
|
qui predict `latent'*,latent se(`selatent'*)
|
||
|
|
|
||
|
|
if "`genlt'"!="" {
|
||
|
|
if `timemax'==1 {
|
||
|
|
qui gen `genlt'=`latent'`i'
|
||
|
|
qui gen `genlt'_se=`selatent'`i'
|
||
|
|
}
|
||
|
|
forvalues t=2/`timemax' {
|
||
|
|
qui gen `genlt'`t'=`latent'`t'
|
||
|
|
qui gen `genlt'`t'_se=`selatent'`t'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
set seed 123456
|
||
|
|
if `timemax'>1 {
|
||
|
|
forvalues t=1/`timemax'{
|
||
|
|
qui gen `latent2'`t'=`latent'`t'+invnorm(uniform())*`selatent'`t'
|
||
|
|
local listit
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local listit `listit' ``i''`t'
|
||
|
|
}
|
||
|
|
qui genscore `listit',score(`score'`t')
|
||
|
|
qui gengroup `latent'`t',newvariable(`group'`t') continuous minsize(`minsize')
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
qui gen `latent2'=`latent'+invnorm(uniform())*`selatent'
|
||
|
|
local listit
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local listit `listit' ``i''
|
||
|
|
}
|
||
|
|
qui genscore `listit',score(`score')
|
||
|
|
qui gengroup `latent',newvariable(`group') continuous minsize(`minsize')
|
||
|
|
}
|
||
|
|
forvalues s=0/`scoremax' {
|
||
|
|
qui count if `score'==`s'
|
||
|
|
local effscore`s'=r(N)
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
/*time 1 only*/
|
||
|
|
qui levelsof `group'`multivisit'
|
||
|
|
local nbgroups=r(r)
|
||
|
|
matrix `groups'=J(`nbgroups',`=`nbitems'+6',.)
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
matrix `groups'[`g',`=`nbitems'+3']=0
|
||
|
|
qui count if `group'`multivisit'==`g'
|
||
|
|
local effgroup`g'=r(N)
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
qui count if ``i''`multivisit'!=.&`group'`multivisit'==`g'
|
||
|
|
local n=r(N)
|
||
|
|
if `n'>0 {
|
||
|
|
qui su ``i''`multivisit' if `group'`multivisit'==`g'
|
||
|
|
matrix `groups'[`g',`i']=r(mean)
|
||
|
|
matrix `groups'[`g',`=`nbitems'+3']=`groups'[`g',`=`nbitems'+3']+`r(mean)'
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
matrix `groups'[`g',`i']=.
|
||
|
|
matrix `groups'[`g',`=`nbitems'+3']=.
|
||
|
|
}
|
||
|
|
}
|
||
|
|
qui su `latent'`multivisit' if `group'`multivisit'==`g'
|
||
|
|
matrix `groups'[`g',`=`nbitems'+1']=r(mean)
|
||
|
|
qui count if `group'`multivisit'==`g'
|
||
|
|
matrix `groups'[`g',`=`nbitems'+2']=r(N)
|
||
|
|
qui su `score' if `group'`multivisit'==`g'&`score'!=.
|
||
|
|
matrix `groups'[`g',`=`nbitems'+4']=r(min)
|
||
|
|
matrix `groups'[`g',`=`nbitems'+5']=r(max)
|
||
|
|
}
|
||
|
|
|
||
|
|
/*number of non-missing on all time points*/
|
||
|
|
egen `miss'=rowmiss(`score'*)
|
||
|
|
qui count if `miss'==0
|
||
|
|
local nbobsssmd=r(N)
|
||
|
|
drop `miss'
|
||
|
|
|
||
|
|
di
|
||
|
|
di as text "Number of individuals:" %6.0f as result `nbobs'
|
||
|
|
di as text "Number of complete individuals:" %6.0f as result `nbobsssmd'
|
||
|
|
di as text "Number of items:" %6.0f as result `nbitems'
|
||
|
|
|
||
|
|
di as text "Marginal log-likelihood:" %12.4f as result `ll'
|
||
|
|
di
|
||
|
|
return scalar ll=`ll'
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
*set trace on
|
||
|
|
/*************************************************************************************************************
|
||
|
|
RECUPERATION DES ESTIMATIONS DES PARAMETRES DE DIFFICULTE
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
tempname diff diffmat vardiff diffmat2
|
||
|
|
*set trace on
|
||
|
|
qui matrix `diffmat'=J(`nbitems',`modamax',.)
|
||
|
|
qui matrix `diffmat2'=J(`nbitems',`modamax',.)
|
||
|
|
qui matrix `diff'=J(`nbdiff',6,.)
|
||
|
|
local rn
|
||
|
|
*qui matrix `vardiff'=J(`nbdiff',`nbdiff',.)
|
||
|
|
*matrix list `diff'
|
||
|
|
*set trace on
|
||
|
|
local t=1
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
qui matrix `diffmat'[`i',1]=-_b[1.``i''`multivisit':_cons]
|
||
|
|
qui matrix `diffmat2'[`i',1]=-_b[1.``i''`multivisit':_cons]
|
||
|
|
qui lincom -_b[1.``i''`multivisit':_cons]
|
||
|
|
qui matrix `diff'[`t',1]=`r(estimate)'
|
||
|
|
qui matrix `diff'[`t',2]=`r(se)'
|
||
|
|
qui matrix `diff'[`t',3]=`r(z)'
|
||
|
|
qui matrix `diff'[`t',4]=`r(p)'
|
||
|
|
qui matrix `diff'[`t',5]=`r(lb)'
|
||
|
|
qui matrix `diff'[`t',6]=`r(ub)'
|
||
|
|
local rn `rn' 1.``i''`multivisit'
|
||
|
|
local ++t
|
||
|
|
local sum _b[1.``i''`multivisit':_cons]
|
||
|
|
if "`rsm'"=="" {
|
||
|
|
forvalues k=2/`modamax`i'' {
|
||
|
|
local sum "_b[`k'.``i''`multivisit':_cons]-(`sum')"
|
||
|
|
*di "``i''`multivisit' `k' `sum'"
|
||
|
|
local sum2 "_b[`=`k'-1'.``i''`multivisit':_cons]-_b[`k'.``i''`multivisit':_cons]"
|
||
|
|
qui lincom (`sum2')
|
||
|
|
*set trace on
|
||
|
|
qui matrix `diffmat'[`i',`k']=`r(estimate)'
|
||
|
|
qui matrix `diffmat2'[`i',`k']=`diffmat2'[`i',`=`k'-1']+`diffmat'[`i',`k']
|
||
|
|
qui matrix `diff'[`t',1]=`r(estimate)'
|
||
|
|
qui matrix `diff'[`t',2]=`r(se)'
|
||
|
|
qui matrix `diff'[`t',3]=`r(z)'
|
||
|
|
qui matrix `diff'[`t',4]=`r(p)'
|
||
|
|
qui matrix `diff'[`t',5]=`r(lb)'
|
||
|
|
qui matrix `diff'[`t',6]=`r(ub)'
|
||
|
|
*qui matrix `vardiff'[`t',`t']=`r(se)'^2
|
||
|
|
*set trace off
|
||
|
|
local rn `rn' `k'.``i''`multivisit'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
if "`rsm'"!="" {
|
||
|
|
forvalues k=2/`modamax' {
|
||
|
|
qui lincom _b[`=`k'-1'.`1'`multivisit':_cons]-_b[`k'.`1'`multivisit':_cons]+_b[1.`1'`multivisit':_cons] /*``i'' instead of `i'?*/
|
||
|
|
qui matrix `diff'[`t',1]=`r(estimate)'
|
||
|
|
qui matrix `diff'[`t',2]=`r(se)'
|
||
|
|
qui matrix `diff'[`t',3]=`r(z)'
|
||
|
|
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, MOYENNES ET VARIANCES
|
||
|
|
*************************************************************************************************************/
|
||
|
|
tempname covariates
|
||
|
|
local nbcov=0
|
||
|
|
forvalues j=2/`timemax'{
|
||
|
|
local nbcov=`nbcov'+`j'-1
|
||
|
|
}
|
||
|
|
qui matrix `covariates'=J(`=`nbpar'+`timemax'+2*`nbcov'',6,.)
|
||
|
|
|
||
|
|
*set trace on
|
||
|
|
local t=1
|
||
|
|
|
||
|
|
|
||
|
|
forvalues j=1/`=`timemax'-1'{
|
||
|
|
forvalues k=`=`j'+1'/`timemax'{
|
||
|
|
if "`categorical'"=="" & "`continuous'"=="" {
|
||
|
|
if `j'==1{
|
||
|
|
qui lincom [/]mean(T`k')
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
qui lincom [/]mean(T`k')-[/]mean(T`j')
|
||
|
|
}
|
||
|
|
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
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
if "`categorical'"!=""{
|
||
|
|
local first=0
|
||
|
|
foreach l in `levelsof`cat1'' {
|
||
|
|
if `first'==0 {
|
||
|
|
local ++first
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
if `first'==1 {
|
||
|
|
qui lincom [T`k']`l'.`cat1'-[T`j']`l'.`cat1'
|
||
|
|
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
|
||
|
|
local ++first
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
qui lincom [T`k']`cont1'-[T`j']`cont1'
|
||
|
|
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 j=1/`timemax'{
|
||
|
|
if "`continuous'"!=""|"`categorical'"!="" {
|
||
|
|
qui lincom _b[/var(e.T`j')]
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
qui lincom _b[/var(T`j')]
|
||
|
|
}
|
||
|
|
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 j=1/`=`timemax'-1'{
|
||
|
|
if "`continuous'"!=""|"`categorical'"!="" {
|
||
|
|
forvalues k=`=`j'+1'/`timemax'{
|
||
|
|
qui lincom _b[/cov(e.T`j',e.T`k')]
|
||
|
|
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
|
||
|
|
}
|
||
|
|
}
|
||
|
|
else{
|
||
|
|
forvalues k=`=`j'+1'/`timemax'{
|
||
|
|
qui lincom _b[/cov(T`j',T`k')]
|
||
|
|
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/ `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 83}"
|
||
|
|
di as text _col(70) "<--95% IC -->"
|
||
|
|
di _col(70) "Lower" _col(78) "Upper"
|
||
|
|
di "Items" _col(22) "Threshold" _col(35) "Estimate" _col(47) "s.e." _col(58) "z" _col(66) "p" _col(69) " Bound" _col(78) "Bound"
|
||
|
|
di "{hline 83}"
|
||
|
|
*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(30) %5.2f "`j'" as result _col(38) %5.2f `diff'[`t',1] _col(46) %5.2f `diff'[`t',2] _col(54) %5.2f `diff'[`t',3] _col(62) %5.2f `diff'[`t',4] _col(70) %5.2f `diff'[`t',5] _col(78) %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(38) %5.2f `diff'[`t',1] _col(46) %5.2f `diff'[`t',2] _col(54) %5.2f `diff'[`t',3] _col(62) %5.2f `diff'[`t',4] _col(70) %5.2f `diff'[`t',5] _col(78) %5.2f `diff'[`t',6]
|
||
|
|
local diffname `diffname' tau`k'
|
||
|
|
local ++t
|
||
|
|
}
|
||
|
|
}
|
||
|
|
di as text "{hline 83}"
|
||
|
|
local t=1
|
||
|
|
local listmoy
|
||
|
|
local listvar
|
||
|
|
local listcov
|
||
|
|
forvalues j=1/`timemax'{
|
||
|
|
local listvar `listvar' Variance_T`j'
|
||
|
|
forvalues k=`=`j'+1'/`timemax'{
|
||
|
|
local listcov `listcov' Cov_T`j'_T`k'
|
||
|
|
}
|
||
|
|
forvalues k=`=`j'+1'/`timemax'{
|
||
|
|
local listmoy `listmoy' Mean_diff_T`j'_T`k'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local n: word count `listmoy' `listvar' `listcov' `continuous'
|
||
|
|
forvalues i=1/`n' {
|
||
|
|
local v: word `i' of `listmoy' `listvar' `listcov' `continuous'
|
||
|
|
di as text _col(1) %5.2f "`v'" as result _col(38) %5.2f `covariates'[`t',1] _col(46) %5.2f `covariates'[`t',2] _col(54) %5.2f `covariates'[`t',3] _col(62) %5.2f `covariates'[`t',4] _col(70) %5.2f `covariates'[`t',5] _col(78) %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(30) %5.2f "`j'" as result _col(38) %5.2f `covariates'[`t',1] _col(46) %5.2f `covariates'[`t',2] _col(54) %5.2f `covariates'[`t',3] _col(62) %5.2f `covariates'[`t',4] _col(70) %5.2f `covariates'[`t',5] _col(78) %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 83}"
|
||
|
|
if "`visit'"==""{
|
||
|
|
di
|
||
|
|
qui su `latent'
|
||
|
|
*qui local PSI=1-(`r(sd)')^2/((`covariates'[1,1])+(`r(sd)')^2)
|
||
|
|
*di as text "Variance of the estimated latent variable: " as result %4.2f `=(`r(sd)')^2'
|
||
|
|
tempvar se2latent
|
||
|
|
qui gen `se2latent'=(`selatent')^2
|
||
|
|
qui su `se2latent'
|
||
|
|
local resvar=r(mean)
|
||
|
|
di as text "Mean squared std error of the latent variable: " as result %4.2f `resvar'
|
||
|
|
di as text "Global variance of the latent variable: " as result %4.2f `=((`covariates'[1,1])+(`resvar'))'
|
||
|
|
local PSI=(`covariates'[1,1])/((`covariates'[1,1])+(`resvar'))
|
||
|
|
di as text "PSI: " as result %4.2f `PSI' _c
|
||
|
|
if "`continuous'"!=""|"`categorical'"!="" {
|
||
|
|
di as text " (without adjustment on covariates)"
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
di
|
||
|
|
}
|
||
|
|
di
|
||
|
|
return scalar PSI=`PSI'
|
||
|
|
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
matrix colnames `covariates'=`cn'
|
||
|
|
matrix rownames `covariates'=`rn'
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
FIT TESTS
|
||
|
|
*************************************************************************************************************/
|
||
|
|
if "`visit'"==""{
|
||
|
|
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)
|
||
|
|
*qui count if `group'==`g'
|
||
|
|
*local eff=r(N)
|
||
|
|
*di "chi2_`g'_``i''=`chi2'+/*`eff'**/(`n1'-`n2')^2/(`d')"
|
||
|
|
local chi2=`chi2'+/*`eff'**/(`n1'-`n2')^2/(`d')
|
||
|
|
local chi2_``i''=`chi2_``i'''+/*`eff'**/(`n1'-`n2')^2/(`d')
|
||
|
|
local chi2_g`g'=`chi2_g`g''+/*`eff'**/(`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 "``i''" _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
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
ESTIMATION OF THE CORRECTED ML ESTIMATORS
|
||
|
|
**************************************************************************************************************/
|
||
|
|
*set trace on
|
||
|
|
tempfile savefile
|
||
|
|
qui save `savefile'
|
||
|
|
|
||
|
|
qui drop _all
|
||
|
|
|
||
|
|
qui set obs 2000
|
||
|
|
qui gen u=(_n-1000)/200*`=sqrt(`covariates'[1,1])'
|
||
|
|
qui gen Tcum=0
|
||
|
|
qui gen TInf=0
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local d=1
|
||
|
|
qui gen cum``i''=0
|
||
|
|
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')
|
||
|
|
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'
|
||
|
|
}
|
||
|
|
qui gen Inf``i''=0
|
||
|
|
forvalues k=1/`mm' {
|
||
|
|
qui replace Inf``i''=Inf``i''+(`k'-cum``i'')^2*c`k'_``i''
|
||
|
|
}
|
||
|
|
qui replace Tcum=Tcum+cum``i''
|
||
|
|
qui replace TInf=TInf+Inf``i''
|
||
|
|
local scoremax=0
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local scoremax=`scoremax'+`modamax`i''
|
||
|
|
}
|
||
|
|
qui gen ecart=.
|
||
|
|
forvalues i=0/`scoremax' {
|
||
|
|
if `i'==0 {
|
||
|
|
local j=0.25
|
||
|
|
}
|
||
|
|
else if `i'==`scoremax' {
|
||
|
|
local j=`scoremax'-0.25
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local j=`i'
|
||
|
|
}
|
||
|
|
qui replace ecart=abs(Tcum-`j')
|
||
|
|
qui su ecart
|
||
|
|
local tmp=r(min)
|
||
|
|
qui su u if round(ecart, 0.01)==round(`tmp',0.01)
|
||
|
|
local estlt`i'=`r(mean)'
|
||
|
|
}
|
||
|
|
qui drop ecart
|
||
|
|
}
|
||
|
|
qui use `savefile', clear
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
RESULTS BY GROUP
|
||
|
|
*************************************************************************************************************/
|
||
|
|
if "`visit'"==""{
|
||
|
|
*set trace on
|
||
|
|
tempname matscorelt
|
||
|
|
qui matrix `matscorelt'=J(`=`nbitems'*`modamax'+1',3,.)
|
||
|
|
di
|
||
|
|
di as text "{hline 71}"
|
||
|
|
di _col(32) "Latent Trait" _col(50) "Expected" _col(63) "Corrected"
|
||
|
|
di "Group" _col(10) "Score" _col(20) "Freq" _col(32) "Mean" _col(42) "s.e." _col(53) "Score" _col(60) "latent trait"
|
||
|
|
di as text "{hline 71}"
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
local sumuc=0
|
||
|
|
local sumc=0
|
||
|
|
qui count if `group'`multivisit'==`g'
|
||
|
|
local eff`g'=r(N)
|
||
|
|
qui count if `group'`multivisit'==`g'&`score'`multivisit'!=.
|
||
|
|
local effcompleted`g'=r(N)
|
||
|
|
qui count if `score'`multivisit'!=.&`group'`multivisit'==`g'
|
||
|
|
local n=r(N)
|
||
|
|
di as text "`g' (n=" as result `eff`g'' as text ")" _c
|
||
|
|
if `n'>0 {
|
||
|
|
qui su `score'`multivisit' if `group'`multivisit'==`g'
|
||
|
|
local scoremin`g'=`r(min)'
|
||
|
|
local scoremax`g'=`r(max)'
|
||
|
|
forvalues s=`scoremin`g''/`scoremax`g'' {
|
||
|
|
qui count if `group'`multivisit'==`g'&`score'`multivisit'==`s'
|
||
|
|
local eff=r(N)
|
||
|
|
if `eff'!=0 {
|
||
|
|
qui su `latent' if `group'`multivisit'==`g'&`score'`multivisit'==`s'
|
||
|
|
local mean=r(mean)
|
||
|
|
*di "local sumc=`sumc'+(`eff')*(`estlt`s'')"
|
||
|
|
*di "local sumuc=`sumuc'+(`eff')*(`mean')"
|
||
|
|
local sumuc=(`sumuc'+((`eff')*(`mean')))
|
||
|
|
local sumc=(`sumc'+((`eff')*(`estlt`s'')))
|
||
|
|
}
|
||
|
|
qui su `selatent' if `group'`multivisit'==`g'&`score'`multivisit'==`s'
|
||
|
|
local se=r(mean)
|
||
|
|
qui su `Tcum' if `group'`multivisit'==`g'&`score'`multivisit'==`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' _col(66) %6.3f `estlt`s''
|
||
|
|
}
|
||
|
|
qui matrix `matscorelt'[`=`s'+1',1]=`s'
|
||
|
|
qui matrix `matscorelt'[`=`s'+1',2]=`mean'
|
||
|
|
qui matrix `matscorelt'[`=`s'+1',3]=`se'
|
||
|
|
}
|
||
|
|
|
||
|
|
}
|
||
|
|
qui count if `group'`multivisit'==`g'&`score'`multivisit'==.
|
||
|
|
local eff=r(N)
|
||
|
|
|
||
|
|
qui su `latent' if `group'`multivisit'==`g'&`score'`multivisit'==.
|
||
|
|
local mean=r(mean)
|
||
|
|
local sumuc=(`sumuc'+((`eff')*(`mean')))
|
||
|
|
qui su `selatent' if `group'`multivisit'==`g'&`score'`multivisit'==.
|
||
|
|
local se=r(mean)
|
||
|
|
qui su `Tcum' if `group'`multivisit'==`g'&`score'`multivisit'==.
|
||
|
|
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 "local lt`g'=`sumuc'/`eff`g''"
|
||
|
|
*di "local clt`g'=`sumc'/`eff`g''"
|
||
|
|
local lt`g'=(`sumuc')/(`eff`g'')
|
||
|
|
local clt`g'=(`sumc')/(`effcompleted`g'')
|
||
|
|
matrix `groups'[`g',`=`nbitems'+6']=`clt`g''
|
||
|
|
*di "group `g' est=`lt`g'' corrected est=`clt`g''"
|
||
|
|
di as text " " "{dup 62:-}"
|
||
|
|
di as text _col(10) "`scoremin`g''/`scoremax`g''" as result _col(20) %4.0f `eff`g'' _col(30) %6.3f `lt`g'' _col(66) %6.3f `clt`g''
|
||
|
|
di as text "{hline 71}"
|
||
|
|
}
|
||
|
|
*matrix list `matscorelt'
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
Categories/Items/Test Characteristics Curves and Information graphs
|
||
|
|
*************************************************************************************************************/
|
||
|
|
*set trace on
|
||
|
|
if "`visit'"==""{
|
||
|
|
if "`graphs'"!=""|"`graphs'"=="" {
|
||
|
|
|
||
|
|
tempfile savefile
|
||
|
|
qui save `savefile'
|
||
|
|
|
||
|
|
*qui clear
|
||
|
|
qui drop _all
|
||
|
|
|
||
|
|
qui set obs 2000
|
||
|
|
qui gen u=(_n-1000)/200*`=sqrt(`covariates'[1,1])'
|
||
|
|
qui gen Tcum=0
|
||
|
|
qui gen TInf=0
|
||
|
|
qui gen ecartcum=.
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local scatteri`i'
|
||
|
|
local scatteric`i'
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
local x=`groups'[`g',`=`nbitems'+1']
|
||
|
|
local xc=`groups'[`g',`=`nbitems'+6']
|
||
|
|
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)
|
||
|
|
local scatteric`i' `scatteric`i'' || scatteri `y' `xc' , 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')"
|
||
|
|
}
|
||
|
|
forvalues k=0/`mm' {
|
||
|
|
if `k'==0 {
|
||
|
|
local l=0.25
|
||
|
|
}
|
||
|
|
else if `k'==`mm' {
|
||
|
|
local l=`k'-0.25
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local l=`k'
|
||
|
|
}
|
||
|
|
qui replace ecartcum=abs(cum``i''-`l')
|
||
|
|
qui su ecartcum
|
||
|
|
qui su u if round(ecartcum,0.01)==round(`r(min)',0.01)
|
||
|
|
local bestest``i''_`k'=r(mean)
|
||
|
|
*di "item ``i'' cat `k' : est=`bestest``i''_`k''"
|
||
|
|
}
|
||
|
|
qui gen Inf``i''=0
|
||
|
|
forvalues k=0/`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)
|
||
|
|
}
|
||
|
|
if "`graphs'"!="" {
|
||
|
|
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 graph twoway line cum``i'' u, name(ICCc``i'',replace) title("Item Characteristic Curve (ICC) of ``i''") ytitle("Score to the item") xtitle("Corrected latent trait") `scatteric`i'' `fsi'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
qui replace Tcum=Tcum+cum``i''
|
||
|
|
*tab Tcum
|
||
|
|
qui replace TInf=TInf+Inf``i''
|
||
|
|
label variable Inf``i'' "``i''"
|
||
|
|
}
|
||
|
|
local scoremax=0
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local scoremax=`scoremax'+`modamax`i''
|
||
|
|
}
|
||
|
|
qui gen ecart=.
|
||
|
|
forvalues i=0/`scoremax' {
|
||
|
|
if `i'==0 {
|
||
|
|
local j=0.25
|
||
|
|
}
|
||
|
|
else if `i'==`scoremax' {
|
||
|
|
local j=`scoremax'-0.25
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local j=`i'
|
||
|
|
}
|
||
|
|
qui replace ecart=abs(Tcum-`j')
|
||
|
|
qui su ecart
|
||
|
|
local tmp=r(min)
|
||
|
|
qui su u if round(ecart, 0.01)==round(`tmp',0.01)
|
||
|
|
local estlt`i'=`r(mean)'
|
||
|
|
*di "score `i' : `r(mean)'"
|
||
|
|
}
|
||
|
|
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)
|
||
|
|
}
|
||
|
|
if "`graphs'"!="" {
|
||
|
|
qui save "C:\temp\info\info",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
|
||
|
|
local scatteric
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
local x=`groups'[`g',`=`nbitems'+1']
|
||
|
|
local xc=`groups'[`g',`=`nbitems'+6']
|
||
|
|
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)
|
||
|
|
local scatteric `scatteric' || scatteri `y' `xc' , mcolor(black) msize(`s') legend(off)
|
||
|
|
}
|
||
|
|
if "`graphs'"!="" {
|
||
|
|
qui graph twoway line Tcum u , name(TCCeo,replace) title("Test Characteristic Curve (TCC)") ytitle("Score to the test") xtitle("Latent trait") `scatteri' `fsteo'
|
||
|
|
qui graph twoway line Tcum u , name(TCCceo,replace) title("Test Characteristic Curve (TCC)") ytitle("Score to the test") xtitle("Corrrected latent trait") `scatteric' `fsteo'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
MAP
|
||
|
|
*************************************************************************************************************/
|
||
|
|
*set trace on
|
||
|
|
if "`graphs'"!="" {
|
||
|
|
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
|
||
|
|
local scatterj
|
||
|
|
local color
|
||
|
|
qui su u if eff!=0
|
||
|
|
*set trace on
|
||
|
|
*set tracedepth 1
|
||
|
|
local floor=floor(`r(min)')
|
||
|
|
local ceil=ceil(`r(max)')
|
||
|
|
local sep
|
||
|
|
local ylbl
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
local color`i':word `i' of `color'
|
||
|
|
local unit=round(`effmax'/`nbitems',1)
|
||
|
|
local y=-`i'*`unit'
|
||
|
|
loca staritem
|
||
|
|
local legend `" 2 "1" "'
|
||
|
|
forvalues l=1/`modamax' {
|
||
|
|
if `l'>=2 {
|
||
|
|
local legend `" `legend' `=2*`l'' "`l'" "'
|
||
|
|
}
|
||
|
|
local x=`diffmat'[`i',`l']
|
||
|
|
local scatteri `scatteri' || scatteri `y' `x' "`l'" ,mcolor(black) mlabcolor(black)
|
||
|
|
if `l'==1 {
|
||
|
|
local xant=`x'
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local xant=`diffmat'[`i',`=`l'-1']
|
||
|
|
}
|
||
|
|
if `xant'>`x' {
|
||
|
|
local star *
|
||
|
|
local staritem *
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
local star
|
||
|
|
}
|
||
|
|
local scatterj `" `scatterj' `sep' scatteri `y' `x' , pstyle(p`l') || pci `y' `xant' `y' `x', pstyle(p1) color(black)"'
|
||
|
|
local sep ||
|
||
|
|
if `x'<`floor' {
|
||
|
|
local floor=floor(`x')
|
||
|
|
}
|
||
|
|
if `x'>`ceil'&`x'!=. {
|
||
|
|
local ceil=ceil(`x')
|
||
|
|
}
|
||
|
|
}
|
||
|
|
local ylbl `ylbl' `=-`i'*`unit'' "``i''`staritem'"
|
||
|
|
local scatteri `scatteri' || scatteri `y' `=`floor'-2' "``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=round(`r(max)', 0.01)+0.01
|
||
|
|
qui drop if u<`floor'|u>`ceil'
|
||
|
|
*di "qui graph twoway (bar eff u, barwidth(.2) yaxis(1) legend(off) xlabel(0(1)`ceil')) (line TInf u,yaxis(2)) (line density u,yaxis(3)) `scatterj' , name(map,replace) ytitle(Frequencies) ylabel(0(`=`maxi'/5')`maxi' ,axis(2)) ylabel(0(`=`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'"
|
||
|
|
*graph combine TIC IIC, col(1)
|
||
|
|
*graph save "map" "map.gph", replace
|
||
|
|
*discard
|
||
|
|
*qui graph twoway line TInf u , name(map,replace)
|
||
|
|
*qui graph twoway `scatterj' , name(map2,replace) ytitle("") ylabel(`ylbl', grid angle(0)) legend(off) xsize(12) ysize(9)
|
||
|
|
qui graph twoway (bar eff u, barwidth(.2) yaxis(1) xlabel(`floor'(1)`ceil') color(erose)) (line TInf u,yaxis(2) lwidth(medthick)) (line density u,yaxis(3) lwidth(medthick) ) `scatterj' , xline(0, lcolor(black)) legend(on order(`"`legend'"') rows(1) subtitle(Threshold parameters) size(small)) name(map,replace) ytitle(" Frequencies") ylabel(0(`=`maxi'/5')`maxi' `maxi'(`maxi')`=`maxi'*2' ,axis(2)) yscale(axis(2) off) yscale(axis(3) off) ylabel(-`maxd'(`=`maxd'/5')`maxd' ,axis(3)) yline(0,lwidth(thick) lcolor(black)) ylabel(`ylbl',/*noticks*/ grid angle(0) axis(1)) ylabel(`ylbl' 0(`=`maxe'/5')`maxe', grid angle(0) axis(1)) title("Individuals/items representations (Map)") xsize(12) ysize(9) note("Red line: Information curve - Green line : Density of the latent trait - * : dysfunctioning items") xtitle("Latent trait") `fsm'
|
||
|
|
*histogram u, name(map,replace)
|
||
|
|
*graph use "map.gph", name(map, replace)
|
||
|
|
*graph combine TIC IIC, xcombine col(1)
|
||
|
|
}
|
||
|
|
qui use `savefile', clear
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
Best estimates by category
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
tempname bestest
|
||
|
|
matrix `bestest'=J(`nbitems',`=`modamax'+1',.)
|
||
|
|
di
|
||
|
|
local long=`modamax'*8+33
|
||
|
|
di "{hline `long'}"
|
||
|
|
di "Item" _col(29) "Cat 0" _c
|
||
|
|
forvalues j=1/`modamax' {
|
||
|
|
local col=29+`j'*8
|
||
|
|
di _col(`col') "Cat `j'" _c
|
||
|
|
}
|
||
|
|
di
|
||
|
|
di "{hline `long'}"
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
di "``i''" _c
|
||
|
|
forvalues j=0/`modamax`i'' {
|
||
|
|
di _col(`=28+`j'*8') %6.3f round(`bestest``i''_`j'', 0.001) _c
|
||
|
|
matrix `bestest'[`i',`=`j'+1']=`bestest``i''_`j''
|
||
|
|
}
|
||
|
|
di
|
||
|
|
}
|
||
|
|
di "{hline `long'}"
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
EQUATING
|
||
|
|
*************************************************************************************************************/
|
||
|
|
*set trace on
|
||
|
|
if "`eqset1'"!="" {
|
||
|
|
|
||
|
|
tokenize `eqset1'
|
||
|
|
local nbset1: word count `eqset1'
|
||
|
|
forvalues i=1/`nbset1' {
|
||
|
|
local eq1_`i':word `i' of `eqset1'
|
||
|
|
*di "set1 (`nbset1') : `eq1_`i''"
|
||
|
|
}
|
||
|
|
*di "`eqset1'"
|
||
|
|
tokenize `eqset2'
|
||
|
|
local nbset2: word count `eqset2'
|
||
|
|
*di "`eqset2'"
|
||
|
|
forvalues i=1/`nbset2' {
|
||
|
|
local eq2_`i':word `i' of `eqset2'
|
||
|
|
*di "set2 (`nbset2') : `eq2_`i''"
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
tempfile fileeq
|
||
|
|
qui save `fileeq',replace
|
||
|
|
forvalues t=1/2{
|
||
|
|
local scoremaxset`t'=0
|
||
|
|
forvalues i=1/`nbset`t'' {
|
||
|
|
*di "`eq`t'_`i''"
|
||
|
|
*local tmp=""
|
||
|
|
local scoremaxset`t'=`scoremaxset`t''+`modamax`eq`t'_`i'''
|
||
|
|
}
|
||
|
|
}
|
||
|
|
drop _all
|
||
|
|
*set trace on
|
||
|
|
qui set obs `=(`scoremaxset1'+`scoremaxset2'+2)*3'
|
||
|
|
forvalues t=1/2 {
|
||
|
|
qui gen scoreset`t'=.
|
||
|
|
qui gen scoreset`t'm=.
|
||
|
|
qui gen scoreset`t'p=.
|
||
|
|
}
|
||
|
|
forvalues i=0/`scoremaxset1' {
|
||
|
|
qui replace scoreset1=`i' in `=`i'+1'
|
||
|
|
qui replace scoreset1m=`i' in `=`i'+1+(`scoremaxset1'+`scoremaxset2'+2)'
|
||
|
|
qui replace scoreset1p=`i' in `=`i'+1+(`scoremaxset1'+`scoremaxset2'+2)*2'
|
||
|
|
}
|
||
|
|
forvalues i=`=`scoremaxset1'+2'/`=`scoremaxset1'+`scoremaxset2'+2' {
|
||
|
|
qui replace scoreset2=`i'-`scoremaxset1'-2 in `i'
|
||
|
|
qui replace scoreset2m=`i'-`scoremaxset1'-2 in `=`i'+(`scoremaxset1'+`scoremaxset2'+2)'
|
||
|
|
qui replace scoreset2p=`i'-`scoremaxset1'-2 in `=`i'+(`scoremaxset1'+`scoremaxset2'+2)*2'
|
||
|
|
}
|
||
|
|
local s=0
|
||
|
|
local eqset1b
|
||
|
|
foreach i in `eqset1' {
|
||
|
|
qui gen s1_`i'=0
|
||
|
|
forvalues m=1/`modamax`i'' {
|
||
|
|
qui gen s1_`i'_`m'=0 in 1/`=`scoremaxset1'+1'
|
||
|
|
qui replace s1_`i'_`m'=1 if scoreset1>`s' in 1/`=`scoremaxset1'+1'
|
||
|
|
qui replace s1_`i'=s1_`i'+s1_`i'_`m'
|
||
|
|
local ++s
|
||
|
|
}
|
||
|
|
local eqset1b `eqset1b' s1_`i'
|
||
|
|
}
|
||
|
|
local s=0
|
||
|
|
local eqset2b
|
||
|
|
foreach i in `eqset2' {
|
||
|
|
qui gen s2_`i'=0
|
||
|
|
forvalues m=1/`modamax`i'' {
|
||
|
|
qui gen s2_`i'_`m'=0 in `=`scoremaxset1'+2'/`=`scoremaxset1'+`scoremaxset2'+2'
|
||
|
|
qui replace s2_`i'_`m'=1 if scoreset2>`s' in `=`scoremaxset1'+2'/`=`scoremaxset1'+`scoremaxset2'+2'
|
||
|
|
qui replace s2_`i'=s2_`i'+s2_`i'_`m'
|
||
|
|
local ++s
|
||
|
|
}
|
||
|
|
local eqset2b `eqset2b' s2_`i'
|
||
|
|
}
|
||
|
|
tokenize `varlist'
|
||
|
|
tempname diffset1 diffset2
|
||
|
|
*matrix list `diffmat'
|
||
|
|
forvalues t=1/2 {
|
||
|
|
qui matrix `diffset`t''=J(`nbset`t'',`modamax',.)
|
||
|
|
local n=1
|
||
|
|
local listset`t'
|
||
|
|
foreach j in `eqset`t'' {
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
if "`j'"=="``i''" {
|
||
|
|
local listset`t' `listset`t'' `i'
|
||
|
|
forvalues m=1/`modamax' {
|
||
|
|
qui matrix `diffset`t''[`n',`m']=`diffmat'[`i',`m']
|
||
|
|
}
|
||
|
|
local ++n
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
*matrix list `diffset1'
|
||
|
|
*matrix list `diffset2'
|
||
|
|
local var=`covariates'[1,1]
|
||
|
|
qui gen lt=.
|
||
|
|
*qui gen selt=.
|
||
|
|
forvalues t=1/2 {
|
||
|
|
tempname matscorelt`t'
|
||
|
|
qui pcm `eqset`t'b', diff(`diffset`t'') var(`var') minsize(1)
|
||
|
|
qui matrix `matscorelt`t''=r(matscorelt)
|
||
|
|
*di "matscorelt`t':"
|
||
|
|
*matrix list `matscorelt`t''
|
||
|
|
forvalues i=0/`scoremaxset`t'' {
|
||
|
|
qui replace lt=`matscorelt`t''[`=`i'+1',2] if scoreset`t'==`i'
|
||
|
|
qui replace lt=`matscorelt`t''[`=`i'+1',2]+1.96*`matscorelt`t''[`=`i'+1',3] if scoreset`t'p==`i'
|
||
|
|
qui replace lt=`matscorelt`t''[`=`i'+1',2]-1.96*`matscorelt`t''[`=`i'+1',3] if scoreset`t'm==`i'
|
||
|
|
*qui replace selt=`matscorelt`t''[`=`i'+1',3] if scoreset`t'==`i'
|
||
|
|
}
|
||
|
|
qui ipolate scoreset`t' lt, gen(score`t') epolate
|
||
|
|
}
|
||
|
|
qui ipolate scoreset1 lt, gen(score1bis) epolate
|
||
|
|
|
||
|
|
|
||
|
|
*list
|
||
|
|
forvalues t=1/2 {
|
||
|
|
qui replace score`t'=scoreset`t'm if scoreset`t'm!=.
|
||
|
|
qui replace score`t'=scoreset`t'p if scoreset`t'p!=.
|
||
|
|
qui replace score1=score1bis if score1==.
|
||
|
|
qui replace score`t'=0 if score`t'<0
|
||
|
|
qui replace score`t'=`scoremaxset`t'' if score`t'>`scoremaxset`t''
|
||
|
|
}
|
||
|
|
forvalues t=1/2 {
|
||
|
|
tempname matscore`t'
|
||
|
|
qui matrix `matscore`t''=J(`=`scoremaxset`t''+1',7,.)
|
||
|
|
forvalues s=0/`scoremaxset`t'' {
|
||
|
|
qui matrix `matscore`t''[`=`s'+1',1]=`s'
|
||
|
|
qui su lt if scoreset`t'==`s'
|
||
|
|
qui matrix `matscore`t''[`=`s'+1',2]=r(mean)
|
||
|
|
qui su lt if scoreset`t'm==`s'
|
||
|
|
qui matrix `matscore`t''[`=`s'+1',3]=r(mean)
|
||
|
|
qui su lt if scoreset`t'p==`s'
|
||
|
|
qui matrix `matscore`t''[`=`s'+1',4]=r(mean)
|
||
|
|
qui su score`=3-`t'' if scoreset`t'==`s'
|
||
|
|
qui matrix `matscore`t''[`=`s'+1',5]=r(mean)
|
||
|
|
qui su score`=3-`t'' if scoreset`t'm==`s'
|
||
|
|
qui matrix `matscore`t''[`=`s'+1',6]=r(mean)
|
||
|
|
qui su score`=3-`t'' if scoreset`t'p==`s'
|
||
|
|
qui matrix `matscore`t''[`=`s'+1',7]=r(mean)
|
||
|
|
}
|
||
|
|
matrix colnames `matscore`t'' =score`t' lt lt- lt+ score`=3-`t'' score`=3-`t''- score`=3-`t''+
|
||
|
|
*matrix list `matscore`t''
|
||
|
|
di
|
||
|
|
di "{hline 78}"
|
||
|
|
di "EQUATING SET`t' TO SET`=3-`t''"
|
||
|
|
di "{hline 78}"
|
||
|
|
di "Set`t' : `eqset`t''"
|
||
|
|
di "Set`=3-`t'' : `eqset`=3-`t'''"
|
||
|
|
di "{hline 78}"
|
||
|
|
di _col(20) "<----- Latent trait ----->" _col(52) "<------- Score `=3-`t'' --------->"
|
||
|
|
di "Score`t'" _col(20) "Estimated" _col(39) "[95%IC]" _col(52) "Estimated" _col(72) "[95%IC]"
|
||
|
|
di "{hline 78}"
|
||
|
|
forvalues s=0/`scoremaxset`t'' {
|
||
|
|
di %4.0f `matscore`t''[`=`s'+1',1] _col(24) %5.2f `matscore`t''[`=`s'+1',2] _col(33) "[" %5.2f `matscore`t''[`=`s'+1',3] ";" %5.2f `matscore`t''[`=`s'+1',4] "]" _col(56) %5.2f `matscore`t''[`=`s'+1',5] _col(66) "[" %5.2f `matscore`t''[`=`s'+1',6] ";" %5.2f `matscore`t''[`=`s'+1',7] "]"
|
||
|
|
}
|
||
|
|
di "{hline 78}"
|
||
|
|
return matrix score`t'_to_`=3-`t''=`matscore`t''
|
||
|
|
if "`eqgraph'"!="" {
|
||
|
|
*twoway (line lt scoreset1) (line lt scoreset2), name(eq1)
|
||
|
|
*twoway (line scoreset1 scoreset2 lt) , name(eq2)
|
||
|
|
*twoway (line score1 scoreset1m scoreset1p score2), name(eq3)
|
||
|
|
*twoway (line score2 scoreset2m scoreset2p score1), name(eq4)
|
||
|
|
twoway (line score`t' score`=3-`t'' if scoreset`=3-`t''!=.) (line score`t' score`=3-`t'' if scoreset`=3-`t''m!=.) (line score`t' score`=3-`t'' if scoreset`=3-`t''p!=.), title("Equating score of the Set `t' from the Set `=3-`t''") ytitle("Score `t'") xtitle("Score `=3-`t''") ylabel(0(1)`scoremaxset`t'') xlabel(0(1)`scoremaxset`=3-`t''') name(eq`t'to`=3-`t'')
|
||
|
|
*twoway (line score2 score1 if scoreset1!=.) (line score2 score1 if scoreset1m!=.) (line score2 score1 if scoreset1p!=.), name(eq6)
|
||
|
|
}
|
||
|
|
}
|
||
|
|
*save prout, replace
|
||
|
|
*clear
|
||
|
|
|
||
|
|
qui use `fileeq',clear
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
RETOUR AU FICHIER INITIAL ET SAUVEGARDE DES NOUVELLES VARIABLES
|
||
|
|
*************************************************************************************************************/
|
||
|
|
if "`visit'"!="" {
|
||
|
|
tempfile sauv
|
||
|
|
set trace on
|
||
|
|
*tempname corrlatent corrbilatent
|
||
|
|
qui keep `latent'* `selatent'* `id' `visit'
|
||
|
|
qui reshape wide , i(`id') j(`visit')
|
||
|
|
qui sort `id'
|
||
|
|
qui save `sauv', replace
|
||
|
|
restore,preserve
|
||
|
|
if "`replace'"!=""&("`genlt'"!=""|"`geninf'"!="") {
|
||
|
|
capture drop `genlt'
|
||
|
|
capture drop `genlt'_se
|
||
|
|
capture drop `geninf'
|
||
|
|
capture drop `genlt'_corr
|
||
|
|
capture drop `genlt'_opt
|
||
|
|
capture drop `genlt'_opt_se
|
||
|
|
}
|
||
|
|
*su
|
||
|
|
tempname idorder
|
||
|
|
qui gen `idorder'=_n
|
||
|
|
qui sort `id'
|
||
|
|
qui merge 1:1 `id' using `sauv'
|
||
|
|
|
||
|
|
qui sort `idorder'
|
||
|
|
qui drop `idorder'
|
||
|
|
}
|
||
|
|
else {
|
||
|
|
*set trace on
|
||
|
|
*set tracedepth 1
|
||
|
|
if "`genlt'"!="" {
|
||
|
|
qui gen `genlt'_corr=.
|
||
|
|
forvalues s=0/`scoremax' {
|
||
|
|
qui replace `genlt'_corr=`estlt`s'' if `score'==`s'
|
||
|
|
}
|
||
|
|
forvalues g=1/`nbgroups' {
|
||
|
|
qui replace `genlt'_corr=`clt`g'' if `group'==`g'&`genlt'_corr==.
|
||
|
|
}
|
||
|
|
tempvar tmpitem mean nbnonmiss
|
||
|
|
forvalues i=1/`nbitems' {
|
||
|
|
qui gen `tmpitem'_`i'=.
|
||
|
|
forvalues k=0/`modamax' {
|
||
|
|
qui replace `tmpitem'_`i'=`bestest'[`i',`=`k'+1'] if ``i''==`k'
|
||
|
|
}
|
||
|
|
}
|
||
|
|
*su
|
||
|
|
qui egen `genlt'_opt=rowmean(`tmpitem'_*)
|
||
|
|
qui egen `genlt'_opt_se=rowsd(`tmpitem'_*)
|
||
|
|
qui egen `nbnonmiss'=rownonmiss(`tmpitem'_*)
|
||
|
|
qui replace `genlt'_opt_se=sqrt((`genlt'_opt_se^2+`resvar')/`nbnonmiss')
|
||
|
|
}
|
||
|
|
restore,not
|
||
|
|
}
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
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
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
/*************************************************************************************************************
|
||
|
|
RETURNS
|
||
|
|
*************************************************************************************************************/
|
||
|
|
|
||
|
|
|
||
|
|
matrix colnames `diff'=Estimate "s.e." z p lb ul
|
||
|
|
matrix colnames `covariates'=Estimate "s.e." z p lb ul
|
||
|
|
matrix rownames `diff'=`diffname'
|
||
|
|
matrix rownames `covariates'=Variance `continuous' `catname'
|
||
|
|
return matrix difficulties=`diff'
|
||
|
|
return matrix covariates=`covariates'
|
||
|
|
return matrix matscorelt=`matscorelt'
|
||
|
|
return matrix bestest=`bestest'
|
||
|
|
capture restore, not
|
||
|
|
end
|