File restructure #2
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Modules/ado/personal/s/old/simirt11.ado
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Modules/ado/personal/s/old/simirt11.ado
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*! version 1.1 8december2005
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*! Jean-Benoit Hardouin
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************************************************************************************************************
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* Simirt: Simulation of dichotomous data following an IRT model (Rasch model,
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* OPLM, Birnbaum model, 3-PLM, 4-PLM, 5-PAM
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*
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* Version 1 : May 9, 2005 (Jean-Benoit Hardouin)
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* Version 1.1 : December 8, 2005 (Jean-Benoit Hardouin) /*group and deltagroup options*/
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*
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* Jean-benoit Hardouin, Regional Health Observatory of Orl<72>ans - France
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* jean-benoit.hardouin@orscentre.org
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*
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* News about this program : http://anaqol.free.fr
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* FreeIRT Project : http://freeirt.free.fr
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*
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* Copyright 2005 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 simirt , rclass
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version 8.0
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syntax [, NBObs(integer 2000) Dim(string) MU(string) COV(string) DISc(string) DIFf(string) PMIN(string) PMAX(string) ACC(string) clear STOre(string) REPlace PREFix(string) DRAW GRoup(real 0) DELtagroup(real 0)]
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/********************************************************************************
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TESTS
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********************************************************************************/
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if `group'<0|`group'>1 {
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di in red "{p}The {hi:group} option defines a probability. The values defined by this option must be greater (or equal) to 0 and lesser (or equal) to 1.{p_end}"
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error 198
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exit
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}
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if "`clear'"==""&"`store'"=="" {
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di in red "You must use at least one of these two options: clear and/or store."
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error 198
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exit
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}
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if "`dim'"!="" {
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local nbdim:word count `dim'
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if `nbdim'>2 {
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di in red "You can simulate data with one or two dimensions, and you have indicated `nbdim' dimensions in the {hi:dim} option. Please correct it."
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error 198
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exit
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}
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if `nbdim'==1 {
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local dim1=`dim'
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local nbitems=`dim1'
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local dim=1
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}
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else if `nbdim'==2 {
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local dim1:word 1 of `dim'
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local dim2:word 2 of `dim'
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local nbitems=`dim1'+`dim2'
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local dim=2
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}
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else {
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di in red "Your {hi:dim} option is uncorrect, please correct it. This option must indicate one or two integer(s)."
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error 198
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exit
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}
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if "`diff'"!="" {
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local nbdiff:word count `diff'
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if (`nbdiff'==3&`dim'==1)|(`nbdiff'==5&`dim'==2)|`nbdiff'==1 {
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local typediff:word 1 of `diff'
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if "`typediff'"!="gauss"&"`typediff'"!="uniform" {
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local typediff values
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}
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}
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if "`typediff'"=="values"&`nbdiff'!=`nbitems' {
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di in red "You have indicated a number of difficulty parameters ({hi:diff} option) different of the number of items to simulate ({hi:dim} option). Please correct these options."
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error 198
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exit
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}
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}
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if "`diff'"=="" {
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if `dim'==1 {
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local diff gauss 0 1
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}
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else if `dim'==2 {
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local diff gauss 0 1 0 1
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}
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local typediff gauss
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local nbdiff:word count `diff'
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}
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}
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else if "`dim'"==""{
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if "`diff'"=="" {
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di in red "You must indicate the number of items to simulate with the {hi:dim} or the {hi:diff} option(s)."
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error 198
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exit
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}
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else {
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local nbdiff:word count `diff'
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if `nbdiff'!=`nbitems' {
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di in red "You have indicated a number of difficulty parameters ({hi:diff} option) different of the number of items to simulate ({hi:dim} option). Please correct these options."
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error 198
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exit
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}
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}
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}
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if "`draw'"!=""&`dim'!=1 {
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di in red "The {hi:draw} option is available only with unidimensional simulated data."
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error 198
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exit
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}
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if (`group'!=0|`deltagroup'!=0)&`dim'!=1 {
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di in red "The {hi:group} and the {hi:deltagroup} options are available only with unidimensional simulated data."
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error 198
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exit
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}
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if "`prefix'"=="" {
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local prefix item
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}
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local nbprefix:word count `prefix'
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local prefix1:word 1 of `prefix'
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if `dim'==2&`nbprefix'>=2 {
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local prefix2:word 2 of `prefix'
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}
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else if `dim'==2 {
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local prefix2:word 1 of `prefix'
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}
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if `dim'==2&"`prefix1'"=="`prefix2'" {
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local prefix1 `prefix1'A
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local prefix2 `prefix2'B
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}
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*di in ye "dim : `dim' ; diff : `diff' ; nbdiff : `nbdiff'"
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local nbcov:word count `cov'
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if `dim'==1&`nbcov'>1 {
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di in red "You simulate one dimension. You must indicate only the variance of the simulated latent trait in the {hi:cov} option."
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error 198
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exit
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}
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else if `dim'==2&`nbcov'!=3&`nbcov'>0 {
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di in red "You simulate two dimensions. You must indicate exactly 3 values in the {hi:cov} option (Variance of the first simulated latent trait, Variance of the second simulated latent trait, Covariance between the two simulated latent traits)."
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error 198
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exit
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}
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else if `nbcov'==0 {
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if `dim'==1 {
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local cov "1"
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}
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else if `dim'==2 {
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local cov "1 1 0"
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}
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local nbcov:word count `cov'
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}
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if `nbcov'==1 {
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if `cov'<0 {
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di in red "The variance of your latent trait can not be negative. Please correct your {hi:cov} option."
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error 198
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}
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}
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else if `nbcov'==3 {
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local cov1:word 1 of `cov'
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local cov2:word 2 of `cov'
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local cov3:word 3 of `cov'
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local rho=`cov3'/sqrt(`cov1'*`cov2')
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if `cov1'<0|`cov2'<0|`rho'<-1|`rho'>1 {
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di in red "Your covariance matrix defined by the {hi:cov} option is not correct. Please correct it."
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error 198
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exit
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}
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}
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local nbmu:word count `mu'
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if `nbmu'!=`dim'&`nbmu'!=0 {
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di in red "You must indicate as many values in the {hi:mu} option as the number of dimension(s) (`dim')"
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error 198
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exit
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}
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local nbdisc:word count `disc'
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if `nbdisc'!=`nbitems'&`nbdisc'!=0 {
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di in red "You must indicate as many values in the {hi:disc} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
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error 198
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exit
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}
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local nbpmin:word count `pmin'
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if `nbpmin'!=`nbitems'&`nbpmin'!=0 {
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di in red "You must indicate as many values in the {hi:pmin} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
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error 198
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exit
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}
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local nbpmax:word count `pmax'
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if `nbpmax'!=`nbitems'&`nbpmax'!=0 {
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di in red "You must indicate as many values in the {hi:pmax} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
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error 198
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exit
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}
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local nbacc:word count `acc'
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if `nbacc'!=`nbitems'&`nbacc'!=0 {
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di in red "You must indicate as many values in the {hi:acc} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
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error 198
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exit
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}
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preserve
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tempfile saveraschbin
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capture qui save `saveraschbin'
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/********************************************************************************
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PARAMETERS
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********************************************************************************/
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/*
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scalar define hour=real(substr("$S_TIME",1,2))
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scalar define min=real(substr("$S_TIME",4,2))
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scalar define sec=real(substr("$S_TIME",7,2))
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scalar define jour=real(substr("$S_DATE",1,2))
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*/
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local hour=real(substr("$S_TIME",1,2))
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local min=real(substr("$S_TIME",4,2))
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local sec=real(substr("$S_TIME",7,2))
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local jour=real(substr("$S_DATE",1,2))
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if "$seed"!="" {
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global seed2=int($seed)
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}
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else {
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global seed2=0
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}
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global seed=$seed2+256484+`sec'*1000000+`min'*10000+`hour'*100+`jour'
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if $seed>2^31-1 {
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global seed=int($seed/10)
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}
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qui set seed $seed
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if "`typediff'"=="uniform" {
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if `dim'==1 {
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if `nbdiff'==3 {
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local min:word 2 of `diff'
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local max:word 3 of `diff'
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}
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else if `nbdiff'==1 {
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local min=-2
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local max=2
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}
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else {
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di in red "Your {hi:diff} option is uncorrect. Please correct it."
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}
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local diff
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forvalues i=1/`nbitems' {
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local diff `diff' `=`min'+(`max'-`min')*`i'/(`nbitems'+1)'
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}
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}
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if `dim'==2 {
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if `nbdiff'==5 {
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local min1:word 2 of `diff'
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local max1:word 3 of `diff'
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local min2:word 4 of `diff'
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local max2:word 5 of `diff'
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}
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else if `nbdiff'==1 {
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local min1=-2
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local max1=2
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local min2=-2
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local max2=2
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}
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else {
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di in red "Your {hi:diff} option is uncorrect. Please correct it."
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exit
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}
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local diff
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forvalues i=1/`dim1' {
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local diff `diff' `=`min1'+(`max1'-`min1')*`i'/(`dim1'+1)'
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}
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forvalues i=1/`dim2' {
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local diff `diff' `=`min2'+(`max2'-`min2')*`i'/(`dim2'+1)'
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}
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}
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}
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if "`typediff'"=="gauss" {
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if `dim'==1 {
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if `nbdiff'==3 {
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local mean:word 2 of `diff'
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local var:word 3 of `diff'
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}
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else if `nbdiff'==1 {
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local mean=0
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local var=1
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}
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else {
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di in red "Your {hi:diff} option is uncorrect. Please correct it."
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error 198
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exit
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}
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local diff
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forvalues i=1/`nbitems' {
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local tmp=invnorm(`i'/(`nbitems'+1))*sqrt(`var')+`mean'
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local diff `diff' `tmp'
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}
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}
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if `dim'==2 {
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if `nbdiff'==5 {
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local mean1:word 2 of `diff'
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local var1:word 3 of `diff'
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local mean2:word 4 of `diff'
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local var2:word 5 of `diff'
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}
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else if `nbdiff'==1 {
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local mean1=0
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local var1=1
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local mean2=0
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local var2=1
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}
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else {
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di in red "Your {hi:diff} option is uncorrect. Please correct it."
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error 198
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exit
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}
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local diff
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forvalues i=1/`dim1' {
|
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local tmp=invnorm(`i'/(`dim1'+1))*sqrt(`var1')+`mean1'
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local diff `diff' `tmp'
|
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}
|
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forvalues i=1/`dim2' {
|
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local tmp=invnorm(`i'/(`dim2'+1))*sqrt(`var2')+`mean2'
|
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local diff `diff' `tmp'
|
||||
}
|
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}
|
||||
}
|
||||
|
||||
|
||||
tempname matmu matcov matdiff matdisc matpmin matpmax matacc
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matrix define `matdiff'=J(`nbitems',1,0)
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matrix define `matdisc'=J(`nbitems',1,0)
|
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matrix define `matpmin'=J(`nbitems',1,0)
|
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matrix define `matpmax'=J(`nbitems',1,0)
|
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matrix define `matacc'=J(`nbitems',1,0)
|
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matrix define `matmu'=J(`dim',1,0)
|
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matrix define `matcov'=J(`=(`dim'+1)*`dim'/2',1,0)
|
||||
|
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forvalues i=1/`nbitems' {
|
||||
local tmp:word `i' of `diff'
|
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matrix `matdiff'[`i',1]=`tmp'
|
||||
if `nbdisc'!=0 {
|
||||
local tmp:word `i' of `disc'
|
||||
matrix `matdisc'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matdisc'[`i',1]=1
|
||||
}
|
||||
if `nbpmin'!=0 {
|
||||
local tmp:word `i' of `pmin'
|
||||
matrix `matpmin'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matpmin'[`i',1]=0
|
||||
}
|
||||
if `nbpmax'!=0 {
|
||||
local tmp:word `i' of `pmax'
|
||||
matrix `matpmax'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matpmax'[`i',1]=1
|
||||
}
|
||||
if `nbacc'!=0 {
|
||||
local tmp:word `i' of `acc'
|
||||
matrix `matacc'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matacc'[`i',1]=1
|
||||
}
|
||||
}
|
||||
|
||||
if `nbcov'==3|`nbcov'==1 {
|
||||
local tmp:word 1 of `cov'
|
||||
matrix `matcov'[1,1]=`tmp'
|
||||
if `nbcov'==3&`dim'==2 {
|
||||
local tmp:word 2 of `cov'
|
||||
matrix `matcov'[2,1]=`tmp'
|
||||
local tmp:word 3 of `cov'
|
||||
matrix `matcov'[3,1]=`tmp'
|
||||
}
|
||||
}
|
||||
else {
|
||||
matrix `matcov'[1,1]=1
|
||||
if `dim'==2 {
|
||||
matrix `matcov'[2,1]=1
|
||||
matrix `matcov'[3,1]=0
|
||||
}
|
||||
}
|
||||
if (`nbmu'==`dim') {
|
||||
local tmp:word 1 of `mu'
|
||||
matrix `matmu'[1,1]=`tmp'
|
||||
if `dim'==2 {
|
||||
local tmp:word 2 of `mu'
|
||||
matrix `matmu'[2,1]=`tmp'
|
||||
}
|
||||
}
|
||||
if `dim'==2 {
|
||||
local corr=`matcov'[3,1]/sqrt(`matcov'[1,1]*`matcov'[2,1])
|
||||
}
|
||||
|
||||
/********************************************************************************
|
||||
ITEMS CHARACTERISTIC CURVES
|
||||
********************************************************************************/
|
||||
|
||||
|
||||
if "`draw'"!="" {
|
||||
*set trace on
|
||||
drop _all
|
||||
qui set obs 2001
|
||||
qui gen lt1=_n
|
||||
qui replace lt1=(lt1-1001)/1000*4*sqrt(`cov')+`matmu'[1,1]
|
||||
label variable lt1 "Latent trait"
|
||||
local dess
|
||||
|
||||
forvalues i=1/`dim1' {
|
||||
qui gen `prefix1'`i'=`matpmin'[`i',1]+(`matpmax'[`i',1]-`matpmin'[`i',1])*(1/(1+exp(-`matdisc'[`i',1]*(lt1-`matdiff'[`i',1]))))^(`matacc'[`i',1])
|
||||
local dess `dess' (line `prefix'`i' lt1)
|
||||
}
|
||||
graph twoway `dess' , ylabel(0(.25)1) legend(off) ytitle("Probability of a positive response")
|
||||
}
|
||||
|
||||
|
||||
/********************************************************************************
|
||||
SIMULATION
|
||||
********************************************************************************/
|
||||
|
||||
drop _all
|
||||
qui set obs `nbobs'
|
||||
qui gen lt1=invnorm(uniform())
|
||||
if `dim'==2 {
|
||||
qui gen lt2=invnorm(uniform())
|
||||
qui replace lt2=`corr'*lt1+sqrt(1-(`corr')^2)*lt2
|
||||
qui replace lt2=lt2*sqrt(`matcov'[2,1])+`matmu'[2,1]
|
||||
}
|
||||
qui replace lt1=lt1*sqrt(`matcov'[1,1])+`matmu'[1,1]
|
||||
|
||||
if `dim'==1&`group'!=0 {
|
||||
qui gen group=uniform()<`group'
|
||||
qui replace lt1=lt1+`deltagroup'*(1-`group') if group==1
|
||||
qui replace lt1=lt1-`deltagroup'*`group' if group==0
|
||||
}
|
||||
|
||||
di in gr "{hline 75}"
|
||||
di _col(1) in gr "Items" _col(18) "Difficulty" _col(34) "Discr." _col(45) "Pmin" _col(58) "Pmax" _col(73) "Acc"
|
||||
di in gr "{hline 75}"
|
||||
forvalues i=1/`dim1' {
|
||||
qui gen `prefix1'`i'=`matpmin'[`i',1]+(`matpmax'[`i',1]-`matpmin'[`i',1])*(1/(1+exp(-`matdisc'[`i',1]*(lt1-`matdiff'[`i',1]))))^(`matacc'[`i',1])
|
||||
qui replace `prefix1'`i'=uniform()<=`prefix1'`i'
|
||||
di _col(1) in gr "`prefix1'`i'" _col(20) in ye %8.4f `matdiff'[`i',1] _col(32) %8.4f `matdisc'[`i',1] _col(44) %6.4f `matpmin'[`i',1] _col(56) %6.4f `matpmax'[`i',1] _col(68) %8.4f `matacc'[`i',1]
|
||||
}
|
||||
if `dim'==2 {
|
||||
di in gr "{hline 75}"
|
||||
forvalues i=`=`dim1'+1'/`=`dim1'+`dim2'' {
|
||||
qui gen `prefix2'`=`i'-`dim1''=`matpmin'[`i',1]+(`matpmax'[`i',1]-`matpmin'[`i',1])*(1/(1+exp(-`matdisc'[`i',1]*(lt2-`matdiff'[`i',1]))))^(`matacc'[`i',1])
|
||||
qui replace `prefix2'`=`i'-`dim1''=uniform()<=`prefix2'`=`i'-`dim1''
|
||||
di _col(1) in gr "`prefix2'`=`i'-`dim1''" _col(20) in ye %8.4f `matdiff'[`i',1] _col(32) %8.4f `matdisc'[`i',1] _col(44) %6.4f `matpmin'[`i',1] _col(56) %6.4f `matpmax'[`i',1] _col(68) %8.4f `matacc'[`i',1]
|
||||
}
|
||||
}
|
||||
di in gr "{hline 75}"
|
||||
di
|
||||
|
||||
|
||||
|
||||
qui corr lt*,cov
|
||||
local var_1=r(Var_1)
|
||||
return scalar var_1=r(Var_1)
|
||||
if `dim'==2 {
|
||||
local cov_12=r(cov_12)
|
||||
local var_2=r(Var_2)
|
||||
return scalar cov_12=r(cov_12)
|
||||
return scalar var_2=r(Var_2)
|
||||
qui corr lt*
|
||||
local rho=r(rho)
|
||||
return scalar rho=r(rho)
|
||||
}
|
||||
qui su lt1
|
||||
local mean1=r(mean)
|
||||
return scalar mean_1=r(mean)
|
||||
if `dim'==2 {
|
||||
qui su lt2
|
||||
local mean2=r(mean)
|
||||
return scalar mean_2=r(mean)
|
||||
}
|
||||
if `dim'==1&`group'!=0 {
|
||||
qui su lt1 if group==0
|
||||
local mean_0=r(mean)
|
||||
qui su lt1 if group==1
|
||||
local mean_1=r(mean)
|
||||
local delta=`mean_1'-`mean_0'
|
||||
}
|
||||
|
||||
return scalar nbobs=`nbobs'
|
||||
|
||||
di in gr "{hline 50}"
|
||||
di _col(1) in gr "Latent trait" _c
|
||||
if `dim'==2 {
|
||||
di in gr "s"_c
|
||||
}
|
||||
di in gr _col(29) "Theorical" _col(42) "Observed"
|
||||
di in gr "{hline 50}"
|
||||
forvalues i=1/`dim' {
|
||||
di _col(1) in gr "Mean(lt`i')" _col(30) in ye %8.4f `matmu'[`i',1] _col(42) %8.4f `mean`i''
|
||||
di _col(1) in gr "Variance(lt`i')" _col(30) in ye %8.4f `matcov'[`i',1] _col(42) %8.4f `var_`i''
|
||||
}
|
||||
if `dim'==1&`group'!=0 {
|
||||
di _col(1) in gr "Mean(lt1) group 0" _col(30) in ye %8.4f `matmu'[1,1]-`deltagroup'*`group' _col(42) %8.4f `mean_0'
|
||||
di _col(1) in gr "Mean(lt1) group 1" _col(30) in ye %8.4f `matmu'[1,1]+`deltagroup'*(1-`group') _col(42) %8.4f `mean_1'
|
||||
qui count if group==1
|
||||
local prop=r(N)/`nbobs'
|
||||
di _col(1) in gr "Proportion group 1" _col(30) in ye %8.4f `group' _col(42) %8.4f `prop'
|
||||
}
|
||||
if `dim'==2 {
|
||||
di _col(1) in gr "Covariance" _col(30) in ye %8.4f `matcov'[3,1] _col(42) %8.4f `cov_12'
|
||||
di _col(1) in gr "Correlation" _col(31) in ye %7.4f `corr' _col(43) %7.4f `rho'
|
||||
}
|
||||
di in gr "{hline 50}"
|
||||
|
||||
/********************************************************************************
|
||||
CLEAR AND/OR STORE
|
||||
********************************************************************************/
|
||||
|
||||
|
||||
if "`clear'"!="" {
|
||||
restore, not
|
||||
preserve
|
||||
}
|
||||
if "`store'"!="" {
|
||||
save "`store'",`replace'
|
||||
}
|
||||
if "`clear'"=="" {
|
||||
use "`saveraschbin'",replace
|
||||
}
|
||||
end
|
||||
804
Modules/ado/personal/s/old/simirt35.ado
Normal file
804
Modules/ado/personal/s/old/simirt35.ado
Normal file
@ -0,0 +1,804 @@
|
||||
*! version 3.5 May 16, 2013
|
||||
*! Jean-Benoit Hardouin
|
||||
************************************************************************************************************
|
||||
* Simirt: Simulation of dichotomous or polytomous data following an IRT model (Rasch model,
|
||||
* OPLM, Birnbaum model, 3-PLM, 4-PLM, 5-PAM, RSM,PCM)
|
||||
*
|
||||
* Version 1 : May 9, 2005 (Jean-Benoit Hardouin)
|
||||
* Version 1.1 : December 8, 2005 (Jean-Benoit Hardouin) /*group and deltagroup options*/
|
||||
* Version 2 : January 20, 2006 (Jean-Benoit Hardouin) /*Rating Scale model*/
|
||||
* Version 2.1 : Februar 2, 2006 (Jean-Benoit Hardouin) /*Threshold variables*/
|
||||
* Version 2.2 : Februar 8, 2006 (Jean-Benoit Hardouin) /*Correction of an error with the RSM model*/
|
||||
* Version 2.3 : October 22, 2006 (Jean-Benoit Hardouin) /*The "real" rating scale model*/
|
||||
* Version 2.4 : July 7, 2008 (Jean-Benoit Hardouin) /*Title for the graphs*/
|
||||
* Version 3 : October 14, 2008 (Jean-Benoit Hardouin) /*3 dimensions + correction for the mu vector*/
|
||||
* Version 3.1 : December 11, 2008 (Jean-Benoit Hardouin) /*remove an useless output*/
|
||||
* Version 3.2 : November 26, 2009 (Jean-Benoit Hardouin) /*covmatrix option*/
|
||||
* Version 3.3 : October 25, 2011 (Jean-Benoit Hardouin) /*pcm option*/
|
||||
* Version 3.4 : May 7, 2013 (Jean-Benoit Hardouin) /*Minor corrections, norandom option*/
|
||||
* Version 3.5 : May 16, 2013 (Jean-Benoit Hardouin) /*Minor corrections*/
|
||||
*
|
||||
* Jean-benoit Hardouin, phD, Assistant Professor
|
||||
* Team of Biostatistics, Pharmacoepidemiology and Subjective Measures in Health Sciences (UPRES EA 4275 SPHERE)
|
||||
* University of Nantes - Faculty of Pharmaceutical Sciences
|
||||
* France
|
||||
* jean-benoit.hardouin@univ-nantes.fr
|
||||
*
|
||||
* News about this program : http://www.anaqol.org
|
||||
*
|
||||
* Copyright 2005-2006, 2008-2009, 2011, 2013 Jean-Benoit Hardouin
|
||||
*
|
||||
* This program is free software; you can redistribute it and/or modify
|
||||
* it under the terms of the GNU General Public License as published by
|
||||
* the Free Software Foundation; either version 2 of the License, or
|
||||
* (at your option) any later version.
|
||||
*
|
||||
* This program is distributed in the hope that it will be useful,
|
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
* GNU General Public License for more details.
|
||||
*
|
||||
* You should have received a copy of the GNU General Public License
|
||||
* along with this program; if not, write to the Free Software
|
||||
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
|
||||
************************************************************************************************************/
|
||||
program define simirt , rclass
|
||||
version 8.0
|
||||
syntax [, NBObs(integer 2000) Dim(string) MU(string) COV(string) COVMatrix(string) DISc(string) DIFf(string) PMIN(string) PMAX(string) ACC(string) clear STOre(string) REPlace PREFix(string) DRAW GRoup(real 0) noRANDom DELtagroup(real 0) rsm1(string) rsm2(string) THReshold TITle(string) PCM(string) id(string)]
|
||||
|
||||
|
||||
/********************************************************************************
|
||||
TESTS
|
||||
********************************************************************************/
|
||||
|
||||
|
||||
if `group'<0|`group'>1 {
|
||||
di in red "{p}The {hi:group} option defines a probability. The values defined by this option must be greater (or equal) to 0 and lesser (or equal) to 1.{p_end}"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
|
||||
if "`clear'"==""&"`store'"=="" {
|
||||
di in red "You must use at least one of these two options: clear and/or store."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
|
||||
if "`dim'"!="" {
|
||||
local nbdim:word count `dim'
|
||||
if `nbdim'>2&"`covmatrix'"=="" {
|
||||
di in red "You can simulate data with one or two dimensions, and you have indicated `nbdim' dimensions in the {hi:dim} option. Please correct it."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
if "`covmatrix'"!="" {
|
||||
local nbrowcovm=rowsof(`covmatrix')
|
||||
if `nbdim'!=`nbrowcovm' {
|
||||
di in red "{p 0 0 0}You define `nbdim' dimension(s) with the {cmd:dim} option and `nbrowcovm' dimension(s) with the {cmd:covmatrix} option. Please correct that."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
}
|
||||
local nbitems=0
|
||||
forvalues d=1/`nbdim' {
|
||||
local dim`d':word `d' of `dim'
|
||||
local nbitems=`nbitems'+`dim`d''
|
||||
}
|
||||
local dim=`nbdim'
|
||||
|
||||
if "`diff'"!="" {
|
||||
local nbdiff:word count `diff'
|
||||
local tmp:word 1 of `diff'
|
||||
if "`tmp'"=="gauss"|"`tmp'"=="uniform" {
|
||||
local typediff values
|
||||
}
|
||||
else if `nbdiff'!=`nbitems' {
|
||||
di in red "You have indicated a number of difficulty parameters ({hi:diff} option) different of the number of items to simulate ({hi:dim} option). Please correct these options."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
}
|
||||
else if "`diff'"=="" {
|
||||
local diff gauss
|
||||
forvalues d=1/`dim' {
|
||||
local diff `diff' 0 1
|
||||
}
|
||||
local typediff gauss
|
||||
local nbdiff:word count `diff'
|
||||
}
|
||||
}
|
||||
else if "`dim'"==""{
|
||||
if "`diff'"==""&"`pcm'"=="" {
|
||||
di in red "{p 0 0 0}You must indicate the number of items to simulate with the {hi:dim}, the {hi:pcm} or the {hi:diff} option(s)."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
else if "`covmatrix'"!= "" {
|
||||
local nbrowcovm=rowsof(`covmatrix')
|
||||
if `nbrowcovm'>1 {
|
||||
di in red "{p 0 0 0}You have define `nbrowcovm' dimensions with the {hi:covmatrix} option, but you do not affect each item to a specific dimension using the {hi:dim} option. Please define the {hi:dim} option."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
}
|
||||
else if "`pcm'"!="" {
|
||||
local nbitems=rowsof(`pcm')
|
||||
local dim=1
|
||||
local dim1=`nbitems'
|
||||
}
|
||||
else {
|
||||
local nbdiff:word count `diff'
|
||||
local nbitems=`nbdiff'
|
||||
local dim=1
|
||||
local dim1=`nbitems'
|
||||
}
|
||||
}
|
||||
|
||||
if (`group'!=0|`deltagroup'!=0)&`dim'!=1 {
|
||||
di in red "The {hi:group} and the {hi:deltagroup} options are available only with unidimensional simulated data."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
|
||||
if "`prefix'"=="" {
|
||||
local prefix item
|
||||
}
|
||||
|
||||
local nbprefix:word count `prefix'
|
||||
if `nbprefix'!=`dim'&`nbprefix'!=1 {
|
||||
di in red "{p 0 0 0}The {hi:prefix} option is incorrect because the number of defined prefixes (`nbprefix') is different of the number of dimensions (`dim'). Please correct it."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
if `nbprefix'==`dim' {
|
||||
forvalues d=1/`dim' {
|
||||
local prefix`d':word `d' of `prefix'
|
||||
}
|
||||
}
|
||||
else {
|
||||
forvalues d=1/`dim' {
|
||||
local tmp:word `d' of A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
|
||||
local prefix`d' `prefix'`tmp'
|
||||
}
|
||||
}
|
||||
*set trace on
|
||||
if "`covmatrix'"=="" {
|
||||
local nbcov:word count `cov'
|
||||
|
||||
if `dim'==1&`nbcov'>1 {
|
||||
di in red "You simulate one dimension. You must indicate only the variance of the simulated latent trait in the {hi:cov} option."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
else if `dim'==2&`nbcov'!=3&`nbcov'>0 {
|
||||
di in red "You simulate two dimensions. You must indicate exactly 3 values in the {hi:cov} option (Variance of the first simulated latent trait, Variance of the second simulated latent trait, Covariance between the two simulated latent traits)."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
else if `nbcov'==0 {
|
||||
if `dim'==1 {
|
||||
local cov "1"
|
||||
}
|
||||
else if `dim'==2 {
|
||||
local cov "1 1 0"
|
||||
}
|
||||
local nbcov:word count `cov'
|
||||
}
|
||||
|
||||
if `nbcov'==1 {
|
||||
if `cov'<0 {
|
||||
di in red "The variance of your latent trait can not be negative. Please correct your {hi:cov} option."
|
||||
error 198
|
||||
}
|
||||
}
|
||||
else if `nbcov'==3 {
|
||||
local cov1:word 1 of `cov'
|
||||
local cov2:word 2 of `cov'
|
||||
local cov3:word 3 of `cov'
|
||||
local rho=`cov3'/sqrt(`cov1'*`cov2')
|
||||
if `cov1'<0|`cov2'<0|`rho'<-1|`rho'>1 {
|
||||
di in red "Your covariance matrix defined by the {hi:cov} option is not correct. Please correct it."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
}
|
||||
tempname covmatrix2
|
||||
if `dim'==1 {
|
||||
matrix `covmatrix2'=(`cov')
|
||||
}
|
||||
else if `dim'==2 {
|
||||
matrix `covmatrix2'=(`cov1' , `cov3' \ `cov3' , `cov2')
|
||||
}
|
||||
local covmatrix `covmatrix2'
|
||||
*matrix list `covmatrix2'
|
||||
}
|
||||
|
||||
local nbmu:word count `mu'
|
||||
if `nbmu'!=`dim'&`nbmu'!=0 {
|
||||
di in red "You must indicate as many values in the {hi:mu} option as the number of dimension(s) (`dim')"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
local nbdisc:word count `disc'
|
||||
if `nbdisc'!=`nbitems'&`nbdisc'!=0 {
|
||||
di in red "You must indicate as many values in the {hi:disc} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
local nbpmin:word count `pmin'
|
||||
if `nbpmin'!=`nbitems'&`nbpmin'!=0 {
|
||||
di in red "You must indicate as many values in the {hi:pmin} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
local nbpmax:word count `pmax'
|
||||
if `nbpmax'!=`nbitems'&`nbpmax'!=0 {
|
||||
di in red "You must indicate as many values in the {hi:pmax} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
local nbacc:word count `acc'
|
||||
if `nbacc'!=`nbitems'&`nbacc'!=0 {
|
||||
di in red "You must indicate as many values in the {hi:acc} option as items defined by the {hi:dim} and the {hi:diff} options (`nbitems')"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
|
||||
if ("`threshold'"!="")&("`disc'"!=""|"`pmin'"!=""|"`pmax'"!=""|"`acc'"!="") {
|
||||
di in red "If you use the {hi:threshold} option, you cannot define the {hi:disc}, {hi:pmin}, {hi:pmax} or {hi:acc} options"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
if ("`rsm1'"!=""|"`rsm2'"!="")&("`disc'"!=""|"`pmin'"!=""|"`pmax'"!=""|"`acc'"!="") {
|
||||
di in red "If you use the {hi:rsm1} and/or {hi:rsm2} option(s), you cannot define the {hi:disc}, {hi:pmin}, {hi:pmax} or {hi:acc} options"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
if "`rsm2'"!=""&`dim'==1 {
|
||||
di in red "You cannot define the {hi:rsm2} option if you simulate only one dimension"
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
if "`id'"=="" {
|
||||
local id="id"
|
||||
}
|
||||
|
||||
preserve
|
||||
|
||||
tempfile saveraschbin
|
||||
capture qui save `saveraschbin'
|
||||
|
||||
|
||||
|
||||
|
||||
/********************************************************************************
|
||||
PARAMETERS
|
||||
********************************************************************************/
|
||||
|
||||
|
||||
local hour=real(substr("$S_TIME",1,2))
|
||||
local min=real(substr("$S_TIME",4,2))
|
||||
local sec=real(substr("$S_TIME",7,2))
|
||||
local jour=real(substr("$S_DATE",1,2))
|
||||
|
||||
|
||||
|
||||
|
||||
if "$seed"!="" {
|
||||
global seed2=int($seed)
|
||||
}
|
||||
else {
|
||||
global seed2=0
|
||||
}
|
||||
global seed=$seed2+256484+`sec'*1000000+`min'*10000+`hour'*100+`jour'
|
||||
while $seed>2^31-1 {
|
||||
global seed=int($seed/231)
|
||||
}
|
||||
qui set seed $seed
|
||||
|
||||
if "`typediff'"=="uniform" {
|
||||
if `nbdiff'==`=`dim'*2+1' {
|
||||
local min`d':word `=(`d'-1)*2+2' of `diff'
|
||||
local max`d':word `=(`d'-1)*2+3' of `diff'
|
||||
}
|
||||
else if `nbdiff'==1 {
|
||||
local min`d'=-2
|
||||
local max`d'=2
|
||||
}
|
||||
else {
|
||||
di in red "Your {hi:diff} option is uncorrect. Please correct it."
|
||||
exit
|
||||
}
|
||||
local diff
|
||||
forvalues d=1/`dim' {
|
||||
forvalues i=1/`dim`d'' {
|
||||
local diff `diff' `=`min`d''+(`max`d''-`min`d'')*`i'/(`dim`d''+1)'
|
||||
}
|
||||
}
|
||||
}
|
||||
*set trace on
|
||||
if "`typediff'"=="gauss" {
|
||||
if `nbdiff'==`=`dim'*2+1' {
|
||||
forvalues d=1/`dim' {
|
||||
local mean`d':word `=(`d'-1)*2+2' of `diff'
|
||||
local var`d':word `=(`d'-1)*2+3' of `diff'
|
||||
}
|
||||
}
|
||||
else if `nbdiff'==1 {
|
||||
forvalues d=1/`dim' {
|
||||
local mean`d'=0
|
||||
local var`d'=1
|
||||
}
|
||||
}
|
||||
else {
|
||||
di in red "Your {hi:diff} option is uncorrect. Please correct it."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
local diff
|
||||
forvalues d=1/`dim' {
|
||||
forvalues i=1/`dim`d'' {
|
||||
local tmp=invnorm(`i'/(`dim`d''+1))*sqrt(`var`d'')+`mean`d''
|
||||
local diff `diff' `tmp'
|
||||
}
|
||||
}
|
||||
}
|
||||
*set trace off
|
||||
|
||||
forvalues d=1/`dim' {
|
||||
if "`rsm`d''"!="" {
|
||||
local nbrsm`d':word count `rsm`d''
|
||||
forvalues i=2/`=`nbrsm`d''+1' {
|
||||
local rsm`d'`i':word `=`i'-1' of `rsm`d''
|
||||
if "`threshold'"!=""&`rsm`d'`i''<0 {
|
||||
di in red "With the {hi:threshold} option, the numbers defined in the {hi:rsm1} and {hi:rsm2} options must be positive."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
if "`pcm'"!="" {
|
||||
local nbmodas=colsof(`pcm')
|
||||
forvalues j=1/`nbitems' {
|
||||
local pcmpj`j'k0=-999999999999999
|
||||
forvalues k=1/`nbmodas' {
|
||||
local pcmpj`j'k`k'=`pcm'[`j',`k']
|
||||
local tmp=`k'-1
|
||||
if "`threshold'"!=""&`pcmpj`j'k`k''<`pcmpj`j'k`tmp'' {
|
||||
di in red "With the {hi:threshold} option, the difficulties of a given item must increase."
|
||||
error 198
|
||||
exit
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
tempname matmu matcov matdiff matdisc matpmin matpmax matacc
|
||||
matrix define `matdiff'=J(`nbitems',1,0)
|
||||
matrix define `matdisc'=J(`nbitems',1,0)
|
||||
matrix define `matpmin'=J(`nbitems',1,0)
|
||||
matrix define `matpmax'=J(`nbitems',1,0)
|
||||
matrix define `matacc'=J(`nbitems',1,0)
|
||||
matrix define `matmu'=J(`dim',1,0)
|
||||
matrix define `matcov'=J(`=(`dim'+1)*`dim'/2',1,0)
|
||||
|
||||
if "`pcm'"=="" {
|
||||
forvalues i=1/`nbitems' {
|
||||
local tmp:word `i' of `diff'
|
||||
matrix `matdiff'[`i',1]=`tmp'
|
||||
if `nbdisc'!=0 {
|
||||
local tmp:word `i' of `disc'
|
||||
matrix `matdisc'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matdisc'[`i',1]=1
|
||||
}
|
||||
if `nbpmin'!=0 {
|
||||
local tmp:word `i' of `pmin'
|
||||
matrix `matpmin'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matpmin'[`i',1]=0
|
||||
}
|
||||
if `nbpmax'!=0 {
|
||||
local tmp:word `i' of `pmax'
|
||||
matrix `matpmax'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matpmax'[`i',1]=1
|
||||
}
|
||||
if `nbacc'!=0 {
|
||||
local tmp:word `i' of `acc'
|
||||
matrix `matacc'[`i',1]=`tmp'
|
||||
}
|
||||
else {
|
||||
matrix `matacc'[`i',1]=1
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if "`covmatrix'"=="" {
|
||||
if `nbcov'==3|`nbcov'==1 {
|
||||
local tmp:word 1 of `cov'
|
||||
matrix `matcov'[1,1]=`tmp'
|
||||
if `nbcov'==3&`dim'==2 {
|
||||
local tmp:word 2 of `cov'
|
||||
matrix `matcov'[2,1]=`tmp'
|
||||
local tmp:word 3 of `cov'
|
||||
matrix `matcov'[3,1]=`tmp'
|
||||
}
|
||||
}
|
||||
}
|
||||
else if 6==9{
|
||||
matrix `matcov'[1,1]=1
|
||||
if `dim'==2 {
|
||||
matrix `matcov'[2,1]=1
|
||||
matrix `matcov'[3,1]=0
|
||||
}
|
||||
}
|
||||
else if "`covmatrix'"!="" {
|
||||
matrix `matcov'=`covmatrix'
|
||||
}
|
||||
if (`nbmu'==`dim') {
|
||||
* local tmp:word 1 of `mu'
|
||||
* matrix `matmu'[1,1]=`tmp'
|
||||
forvalues d=1/`dim' {
|
||||
local tmp:word `d' of `mu'
|
||||
matrix `matmu'[`d',1]=`tmp'
|
||||
}
|
||||
* if `dim'>1 {
|
||||
* local tmp:word 2 of `mu'
|
||||
* matrix `matmu'[2,1]=`tmp'
|
||||
* }
|
||||
}
|
||||
if `dim'==2 {
|
||||
local corr=`matcov'[3,1]/sqrt(`matcov'[1,1]*`matcov'[2,1])
|
||||
}
|
||||
|
||||
/********************************************************************************
|
||||
ITEMS CHARACTERISTIC CURVES
|
||||
********************************************************************************/
|
||||
|
||||
|
||||
if "`draw'"!="" {
|
||||
*set trace on
|
||||
drop _all
|
||||
qui set obs 2001
|
||||
qui gen lt1=_n
|
||||
qui replace lt1=(lt1-1001)/1000*4*sqrt(`covmatrix'[1,1])+`matmu'[1,1]
|
||||
label variable lt1 "Latent trait"
|
||||
local dess
|
||||
|
||||
|
||||
if "`rsm1'"==""&"`pcm'"=="" {
|
||||
if "`title'"=="" {
|
||||
local title2="Item Characteristics Curves of the items"
|
||||
}
|
||||
else {
|
||||
local title2="`title'"
|
||||
}
|
||||
forvalues i=1/`dim1' {
|
||||
if "`threshold'"=="" {
|
||||
qui gen `prefix1'`i'=`matpmin'[`i',1]+(`matpmax'[`i',1]-`matpmin'[`i',1])*(1/(1+exp(-`matdisc'[`i',1]*(lt1-`matdiff'[`i',1]))))^(`matacc'[`i',1])
|
||||
}
|
||||
else {
|
||||
qui gen `prefix1'`i'=lt1>`matdiff'[`i',1]
|
||||
}
|
||||
local dess `dess' (line `prefix'`i' lt1)
|
||||
}
|
||||
graph twoway `dess' , ylabel(0(.25)1) legend(off) ytitle("Probability of a positive response" title"") title("`title2'")
|
||||
}
|
||||
else if "`pcm'"==""{
|
||||
forvalues i=1/`dim1' {
|
||||
if "`title'"=="" {
|
||||
local title2="Item `i'"
|
||||
}
|
||||
else {
|
||||
local title2="`title'"
|
||||
}
|
||||
local dess
|
||||
local tau0=0
|
||||
local tau1=`matdiff'[`i',1]
|
||||
local D "1+exp(lt`d'-`tau1')"
|
||||
forvalues k=2/`=`nbrsm1'+1' {
|
||||
local tau`k'=`tau`=`k'-1''+`matdiff'[`i',1]+`rsm1`k''
|
||||
local D "`D'+exp(`k'*lt1-`tau`k'') "
|
||||
}
|
||||
forvalues k=`=`nbrsm1'+1'(-1)0 {
|
||||
tempname prob`k'
|
||||
qui gen `prob`k''=exp(`k'*lt1-`tau`k'')/(`D')
|
||||
local dess `dess' (line `prob`k'' lt1)
|
||||
label variable `prob`k'' "`k'"
|
||||
}
|
||||
graph twoway `dess' , ylabel(0(.25)1) legend(on) ytitle("Probability of response to each modality") title("`title2'") name(item`i',replace)
|
||||
}
|
||||
}
|
||||
else if "`pcm'"!=""{
|
||||
forvalues j=1/`dim1' {
|
||||
if "`title'"=="" {
|
||||
local title2="Item `j'"
|
||||
}
|
||||
else {
|
||||
local title2="`title'"
|
||||
}
|
||||
local dess
|
||||
local tauj`j'k0=0
|
||||
forvalues k=1/`nbmodas' {
|
||||
local tauj`j'k`k'=`tauj`j'k`=`k'-1''+`matdiff'[`j',`k']
|
||||
local D "`D'+exp(`k'*lt1-`tauj`j'k`k'') "
|
||||
}
|
||||
forvalues k=`=`nbrsm1'+1'(-1)0 {
|
||||
tempname prob`k'
|
||||
qui gen `prob`k''=exp(`k'*lt1-`tauj`j'k`k'')/(`D')
|
||||
local dess `dess' (line `prob`k'' lt1)
|
||||
label variable `prob`k'' "`k'"
|
||||
}
|
||||
graph twoway `dess' , ylabel(0(.25)1) legend(on) ytitle("Probability of response to each modality") title("`title2'") name(item`i',replace)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/********************************************************************************
|
||||
SIMULATION
|
||||
********************************************************************************/
|
||||
|
||||
|
||||
drop _all
|
||||
qui set obs `nbobs'
|
||||
gen `id'=_n
|
||||
local names
|
||||
forvalues d=1/`dim' {
|
||||
qui gen x`d'=invnorm(uniform())
|
||||
qui compress
|
||||
local names `names' lt`d'
|
||||
}
|
||||
/*mkmat lt1-lt`dim' , matrix(lt)
|
||||
matrix Chol=cholesky(corr(`covmatrix'))
|
||||
*matrix list lt
|
||||
*matrix list Chol
|
||||
matrix lt=lt*Chol'
|
||||
matrix colnames lt=`names'
|
||||
|
||||
*matrix list lt
|
||||
drop _all
|
||||
qui svmat lt*/
|
||||
|
||||
matrix Chol=cholesky(corr(`covmatrix'))
|
||||
forvalues d=1/`dim' {
|
||||
qui gen lt`d'=0
|
||||
forvalues i=1/`d' {
|
||||
qui replace lt`d'=lt`d'+Chol[`d',`i']*x`i'
|
||||
}
|
||||
qui compress
|
||||
}
|
||||
qui drop x*
|
||||
forvalues d=1/`dim' {
|
||||
qui replace lt`d'=lt`d'*sqrt(`covmatrix'[`d',`d'])+`matmu'[`d',1]
|
||||
qui compress
|
||||
}
|
||||
|
||||
if `dim'==1&`group'!=0 {
|
||||
if "`random'"=="" {
|
||||
qui gen group=uniform()<`group'
|
||||
}
|
||||
else {
|
||||
qui gen group=`id'<=`group'*`nbobs'
|
||||
}
|
||||
qui replace lt1=lt1+`deltagroup'*(1-`group') if group==1
|
||||
qui replace lt1=lt1-`deltagroup'*`group' if group==0
|
||||
qui compress
|
||||
}
|
||||
|
||||
di in gr "Number of individuals: " in ye `nbobs'
|
||||
di
|
||||
|
||||
if "`threshold'"==""&"`rsm1'"=="" {
|
||||
local line di in gr "{hline 75}"
|
||||
}
|
||||
else {
|
||||
local line di in gr "{hline 27}"
|
||||
}
|
||||
|
||||
if "`threshold'"==""&"`rsm1'"==""&"`pcm'"=="" {
|
||||
`line'
|
||||
di _col(1) in gr "Items" _col(18) "Difficulty" _col(34) "Discr." _col(45) "Pmin" _col(58) "Pmax" _col(73) "Acc"
|
||||
}
|
||||
else {
|
||||
`line'
|
||||
di _col(1) in gr "Items" _col(18) "Difficulty"
|
||||
}
|
||||
local dim0=0
|
||||
|
||||
*set trace on
|
||||
|
||||
local deb1=1
|
||||
local fin1=`dim1'
|
||||
|
||||
forvalues d=1/`dim' { /* FOREACH DIMENSION*/
|
||||
local deb`d'=`fin`=`d'-1''+1
|
||||
local fin`d'=`deb`d''+`dim`d''-1
|
||||
`line'
|
||||
local p=`d'-1
|
||||
local q=1
|
||||
forvalues i=`deb`d''/`fin`d'' { /*FOREACH ITEM*/
|
||||
*set trace on
|
||||
*local q=`i'-`dim`p''*/
|
||||
qui compress
|
||||
if "`pcm'"=="" {
|
||||
tempname prob`=`nbrsm`d''+2'
|
||||
qui gen `prob`=`nbrsm`d''+2''=0
|
||||
local tau1=`matdiff'[`i',1]
|
||||
local D "1+exp(lt`d'-`tau1')"
|
||||
forvalues k=2/`=`nbrsm`d''+1' {
|
||||
local tau`k'=`tau`=`k'-1''+`matdiff'[`i',1]+`rsm`d'`k''
|
||||
*di "tau`k'=`tau`k''"
|
||||
local D "`D'+exp(`k'*lt`d'-`tau`k'') "
|
||||
}
|
||||
}
|
||||
else {
|
||||
tempname prob`=`nbmodas'+1'
|
||||
qui gen `prob`=`nbmodas'+1''=0
|
||||
local tau1=`pcm'[`i',1]
|
||||
local D "1+exp(lt`d'-`tau1')"
|
||||
forvalues k=2/`nbmodas' {
|
||||
local tau`k'=`tau`=`k'-1''+`pcm'[`i',`k']
|
||||
*di "tau`k'=`tau`k''"
|
||||
local D "`D'+exp(`k'*lt`d'-`tau`k'') "
|
||||
}
|
||||
}
|
||||
if "`threshold'"==""/*&"`rsm1'"==""*/ {
|
||||
if "`rsm`d''"==""&"`pcm'"=="" {
|
||||
tempname prob1
|
||||
qui gen `prob1'=`prob`=`nbrsm`d''+2''+`matpmin'[`i',1]+(`matpmax'[`i',1]-`matpmin'[`i',1])*(1/(1+exp(-`matdisc'[`i',1]*(lt`d'-`matdiff'[`i',1]))))^(`matacc'[`i',1])
|
||||
qui compress
|
||||
}
|
||||
else if "`rsm`d''"!=""{
|
||||
forvalues k=`=`nbrsm`d''+1'(-1)1 {
|
||||
tempname prob`k'
|
||||
qui gen `prob`k''=exp(`k'*lt`d'-`tau`k'')/(`D')+`prob`=`k'+1''
|
||||
qui compress
|
||||
}
|
||||
}
|
||||
else if "`pcm'"!="" {
|
||||
forvalues k=`nbmodas'(-1)1 {
|
||||
tempname prob`k'
|
||||
qui gen `prob`k''=exp(`k'*lt`d'-`tau`k'')/(`D')+`prob`=`k'+1''
|
||||
qui compress
|
||||
}
|
||||
}
|
||||
qui gen `prefix`d''`q'=0
|
||||
if "`rsm1'"==""&"`pcm'"=="" {
|
||||
di _col(1) in gr "`prefix`d''`q'" _col(20) in ye %8.4f `matdiff'[`i',1] _col(32) %8.4f `matdisc'[`i',1] _col(44) %6.4f `matpmin'[`i',1] _col(56) %6.4f `matpmax'[`i',1] _col(68) %8.4f `matacc'[`i',1]
|
||||
}
|
||||
else if "`rsm1'"!="" {
|
||||
di _col(1) in gr "`prefix`d''`q'" _col(20) in ye %8.4f `matdiff'[`i',1]
|
||||
}
|
||||
else if "`pcm'"!="" {
|
||||
forvalues k=1/`nbmodas' {
|
||||
di _col(1) in gr "`prefix`d''`q'_`k'" _col(20) in ye %8.4f `pcm'[`i',`k']
|
||||
}
|
||||
}
|
||||
tempname uni
|
||||
qui gen `uni'=uniform()
|
||||
qui compress
|
||||
if "`pcm'"=="" {
|
||||
forvalues k=1/`=`nbrsm`d''+1' {
|
||||
qui replace `prefix`d''`q'=`k' if `uni'<=`prob`k''
|
||||
qui drop `prob`k''
|
||||
qui compress
|
||||
}
|
||||
}
|
||||
else {
|
||||
forvalues k=1/`nbmodas' {
|
||||
qui replace `prefix`d''`q'=`k' if `uni'<=`prob`k''
|
||||
qui drop `prob`k''
|
||||
qui compress
|
||||
}
|
||||
}
|
||||
}
|
||||
else { /*if "`threshold'"!=""*/
|
||||
if "`pcm'"=="" {
|
||||
di _col(1) in gr "`prefix`d''`q'" _col(20) in ye %8.4f `matdiff'[`i',1]
|
||||
qui gen `prefix`d''`q'=lt`d'>`matdiff'[`i',1]
|
||||
qui compress
|
||||
forvalues k=1/`=`nbrsm`d''+1' {
|
||||
qui replace `prefix`d''`q'=`k' if lt`d'>=`tau`k''
|
||||
qui compress
|
||||
}
|
||||
}
|
||||
else {
|
||||
qui gen `prefix`d''`q'=lt`d'>`pcm'[`i',1]
|
||||
forvalues k=1/`nbmodas' {
|
||||
di _col(1) in gr "`prefix`d''`q'_`k'" _col(20) in ye %8.4f `pcm'[`i',`k']
|
||||
qui replace `prefix`d''`q'=`k' if lt`d'>`pcm'[`i',`k']
|
||||
qui compress
|
||||
}
|
||||
}
|
||||
}
|
||||
local q=`q'+1
|
||||
}
|
||||
forvalues k=2/`=`nbrsm`d''+1' {
|
||||
di _col(1) in gr "tau`k'" _col(20) in ye %8.4f `rsm`d'`k''
|
||||
}
|
||||
}
|
||||
`line'
|
||||
di
|
||||
*set trace on
|
||||
|
||||
|
||||
forvalues d=1/`dim' {
|
||||
qui su lt`d'
|
||||
local var_`d'=r(Var)
|
||||
local mean_`d'=r(mean)
|
||||
forvalues l=`=`d'+1'/`dim' {
|
||||
qui corr lt`d' lt`l' ,cov
|
||||
local cov_`d'_`l'=r(cov_12)
|
||||
return scalar cov_`d'_`l'=`cov_`d'_`l''
|
||||
}
|
||||
return scalar mean_`d'=`mean_`d''
|
||||
return scalar var_`d'=`var_`d''
|
||||
}
|
||||
forvalues d=1/`dim' {
|
||||
forvalues l=`=`d'+1'/`dim' {
|
||||
local corr_`d'_`l'=`cov_`d'_`l''/sqrt(`var_`d''*`var_`l'')
|
||||
return scalar corr_`d'_`l'=`corr_`d'_`l''
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
if `dim'==1&`group'!=0 {
|
||||
qui su lt1 if group==0
|
||||
local mean_0=r(mean)
|
||||
qui su lt1 if group==1
|
||||
local mean_1=r(mean)
|
||||
local delta=`mean_1'-`mean_0'
|
||||
}
|
||||
|
||||
return scalar nbobs=`nbobs'
|
||||
tempname matcorr
|
||||
*matrix list `matcov'
|
||||
matrix `matcorr'=corr(`matcov')
|
||||
|
||||
di in gr "{hline 50}"
|
||||
di _col(1) in gr "Latent trait" _c
|
||||
if `dim'==2 {
|
||||
di in gr "s"_c
|
||||
}
|
||||
di in gr _col(30) "Expected" _col(42) "Observed"
|
||||
di in gr "{hline 50}"
|
||||
forvalues i=1/`dim' {
|
||||
di _col(1) in gr "Mean(lt`i')" _col(30) in ye %8.4f `matmu'[`i',1] _col(42) %8.4f `mean_`i''
|
||||
di _col(1) in gr "Variance(lt`i')" _col(30) in ye %8.4f `matcov'[`i',`i'] _col(42) %8.4f `var_`i''
|
||||
forvalues d=`=`i'+1'/`dim' {
|
||||
di _col(1) in gr "Covariance `i'_`d'" _col(30) in ye %8.4f `matcov'[`i',`d'] _col(42) %8.4f `cov_`i'_`d''
|
||||
di _col(1) in gr "Correlation `i'_`d'" _col(31) in ye %7.4f `matcorr'[`i',`d'] _col(43) %7.4f `corr_`i'_`d''
|
||||
}
|
||||
di in gr "{hline 50}"
|
||||
}
|
||||
if `dim'==1&`group'!=0 {
|
||||
di _col(1) in gr "Mean(lt1) group 0" _col(30) in ye %8.4f `matmu'[1,1]-`deltagroup'*`group' _col(42) %8.4f `mean_0'
|
||||
di _col(1) in gr "Mean(lt1) group 1" _col(30) in ye %8.4f `matmu'[1,1]+`deltagroup'*(1-`group') _col(42) %8.4f `mean_1'
|
||||
qui count if group==1
|
||||
local prop=r(N)/`nbobs'
|
||||
di _col(1) in gr "Proportion group 1" _col(30) in ye %8.4f `group' _col(42) %8.4f `prop'
|
||||
di in gr "{hline 50}"
|
||||
}
|
||||
|
||||
/********************************************************************************
|
||||
CLEAR AND/OR STORE
|
||||
********************************************************************************/
|
||||
qui compress
|
||||
|
||||
if "`clear'"!="" {
|
||||
restore, not
|
||||
preserve
|
||||
}
|
||||
if "`store'"!="" {
|
||||
save "`store'",`replace'
|
||||
}
|
||||
if "`clear'"=="" {
|
||||
use "`saveraschbin'",replace
|
||||
}
|
||||
end
|
||||
71
Modules/ado/personal/s/old/simul2tl2plm.ado
Normal file
71
Modules/ado/personal/s/old/simul2tl2plm.ado
Normal file
@ -0,0 +1,71 @@
|
||||
program define simul2tl2plm
|
||||
version 7.0
|
||||
syntax [, nbobs(integer 2000) dim1(real 7) dim2(real 7) corr(real 0) disc1(real 1) disc2(real 1) sigma1(real 1) sigma2(real 1)]
|
||||
|
||||
scalar define hour=real(substr("$S_TIME",1,2))
|
||||
scalar define min=real(substr("$S_TIME",4,2))
|
||||
scalar define sec=real(substr("$S_TIME",7,2))
|
||||
scalar define jour=real(substr("$S_DATE",1,2))
|
||||
|
||||
if "$seed2"!="" {
|
||||
global seed2=int($seed/100000)}
|
||||
else {
|
||||
global seed2=0
|
||||
}
|
||||
global seed=sec*1000000+min*10000+hour*100+jour+$seed2
|
||||
|
||||
set seed $seed
|
||||
quietly {
|
||||
drop _all
|
||||
set obs `nbobs'
|
||||
gen TL1=invnorm(uniform())*`sigma1'
|
||||
gen TL2=invnorm(uniform())*`sigma2'
|
||||
replace TL2=`corr'*TL1+sqrt(1-`corr'^2)*TL2
|
||||
|
||||
local items=1
|
||||
global rep1
|
||||
while `items'<=`dim1' {
|
||||
local nitems=100+`items'
|
||||
gen diff`nitems'=invnorm(`items'/(`dim1'+1))
|
||||
gen prob`nitems'=1/(1+exp(-1.7*`disc1'*(TL1-diff`nitems')))
|
||||
gen rep`nitems'=0
|
||||
replace rep`nitems'=1 if prob`nitems'>=uniform()
|
||||
global rep1 $rep1 rep`nitems'
|
||||
local items=`items'+1
|
||||
}
|
||||
|
||||
local items=1
|
||||
global rep2
|
||||
while `items'<=`dim2' {
|
||||
local nitems=200+`items'
|
||||
gen diff`nitems'=invnorm(`items'/(`dim2'+1))
|
||||
gen prob`nitems'=1/(1+exp(-1.7*`disc2'*(TL2-diff`nitems')))
|
||||
gen rep`nitems'=0
|
||||
replace rep`nitems'=1 if prob`nitems'>=uniform()
|
||||
global rep2 $rep2 rep`nitems'
|
||||
local items=`items'+1
|
||||
}
|
||||
gen ind=_n
|
||||
keep ind $rep1 $rep2}
|
||||
|
||||
|
||||
quietly{
|
||||
reshape long rep,i(ind) j(item)
|
||||
|
||||
local items=1
|
||||
while `items'<=`dim1' {
|
||||
local nitems=100+`items'
|
||||
gen item`nitems'=0
|
||||
replace item`nitems'=-1 if item==`nitems'
|
||||
local items=`items'+1
|
||||
}
|
||||
local items=1
|
||||
while `items'<=`dim2' {
|
||||
local nitems=200+`items'
|
||||
gen item`nitems'=0
|
||||
replace item`nitems'=-1 if item==`nitems'
|
||||
local items=`items'+1
|
||||
}
|
||||
|
||||
}/*fin du quietly*/
|
||||
end
|
||||
Reference in New Issue
Block a user