Computed theoretical power for N=100 and N=200 scenarios
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291
Modules/ado/personal/c/compart.ado
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291
Modules/ado/personal/c/compart.ado
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program define compart,rclass
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version 8
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syntax varlist [if] [in] [fweight iweight] [,part(numlist) Matrix(string) type(string) DETails noSTANDardized VARiables SQUare]
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preserve
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unab varlist:`varlist'
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di "`varlist'"
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tokenize `varlist'
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marksample touse
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local nbvar:word count `varlist'
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qui count
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local nbind=r(N)
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tempname p
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qui gen `p'=1
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qui su `p' [`weight'`exp'] if `touse'
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local nbind=r(N)
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if "`square'"=="" {
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local quad=1
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}
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else {
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local quad=2
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}
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if "`type'"!=""&"`type'"!="polychoric" {
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di in red "The type of the matrix is not authorized. Please correct your {hi:type} option."
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error 198
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}
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if "`type'"!=""&"`matrix'"!="" {
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di in red "You cannot define in the same time the {hi:type} and the {hi:matrix} options"
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error 198
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}
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/* DEFINITION OF THE PARTITION OF THE VARIABLES*/
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local newpart
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foreach i in `part' {
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if `i'!=0 {
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local newpart `newpart' `i'
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}
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}
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local part `newpart'
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local meme=0
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local diff=0
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local nbpart:word count `part'
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forvalues i=1/`nbpart' {
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local iti:word `i' of `part'
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local meme=`meme'+`iti'*(`iti'-1)/2
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forvalues j=`=`i'+1'/`nbpart' {
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local itj:word `j' of `part'
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local diff=`diff'+`iti'*`itj'
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}
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}
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local perc=`meme'/(`meme'+`diff')
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di "meme: `meme' ; diff: `diff' ; perc: `perc'"
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local test=0
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local last0=0
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forvalues i=1/`nbpart' {
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local first`i'=`last`=`i'-1''+1
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local size`i':word `i' of `part'
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local last`i'=`first`i''+`size`i''-1
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local test=`test'+`size`i''
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local list`i'
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forvalues j=`first`i''/`last`i'' {
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local list`i' `list`i'' ``j''
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}
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}
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if `test'!=`nbvar' {
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di in red "{p}The described partition of the variables is composed of a number of variables different of the number of variables of varlist.{p_end}"
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exit 198
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}
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/* BY DEFAULT, STANDARDIZATION*/
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if "`standardized'"=="" {
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forvalues i=1/`nbvar' {
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qui su ``i'' [`weight'`exp']
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qui replace ``i''=(``i''-r(mean))/r(sd)
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}
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}
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tempname Cov W
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if "`matrix'"==""&"`type'"!="polychoric" {
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/* COVARIANCE OR CORRELATION MATRIX*/
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qui matrix accum `Cov'=`varlist' [`weight'`exp'],nocons dev
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qui matrix `Cov'=`Cov'/(`nbind'-1)
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}
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else if "`type'"=="polychoric" {
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qui polychoric `varlist'
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qui matrix `Cov'=r(R)
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}
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else {
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qui matrix `Cov'=`matrix'
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}
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/* WE SAVE THE MATRIX AND WE COMPUTE THE AVERAGE COVARIANCE */
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qui matrix `W'=`Cov'
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local sum=0
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forvalues i=1/`nbvar' {
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forvalues j=`=`i'+1'/`nbvar' {
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local sum=`sum'+ `W'[`i',`j']^`quad'
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}
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}
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/* WE SAVE THE DATA AND WE COMPUTES THE USED PERCENTILES OF THE COVARIANCE*/
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tempfile compartfile
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qui save `compartfile',replace
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drop _all
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set obs `=`nbvar'*(`nbvar'-1)'
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local n=1
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qui gen i=.
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qui gen j=.
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qui gen corr=.
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forvalues i=1/`nbvar' {
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forvalues j=`=`i'+1'/`nbvar' {
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qui replace i=`i' in `n'
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qui replace j=`j' in `n'
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qui replace corr=`W'[`i',`j']^`quad' in `n'
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local ++n
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}
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}
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matrix list `W'
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su corr
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sort corr
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centile corr,centile(`=100-`perc'*100')
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local centile=r(c_1)
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if `diff'!=0 {
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local perc2=(`meme'+1)/(`meme'+`diff')
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centile corr,centile(`=100-`perc2'*100')
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local centile2=r(c_1)
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local centile=(`centile'+`centile2')/2
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}
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qui use `compartfile',clear
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/***************************************************/
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if `nbpart'==1 {
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local mean=0
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* local mean=(2*`sum')/(`nbvar'*(`nbvar'-1))
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}
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else {
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local mean=(2*`sum')/(`nbvar'*(`nbvar'-1))
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local mean=0
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*local mean=`centile'
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}
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/*THE MATRIX IS CENTERED*/
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forvalues i=1/`nbvar' {
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matrix `W'[`i',`i']=0
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forvalues j=`=`i'+1'/`nbvar' {
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matrix `W'[`i',`j']=(`W'[`i',`j']^`quad'-`mean')
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matrix `W'[`j',`i']=`W'[`i',`j']
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}
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}
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/*WE COMPUTE THE INDEX D*/
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local C=0
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local C1=0
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local C2=0
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local minrho=2
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local summeme=0
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local sumdiff=0
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if "`square'"!="" {
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local maxrho=0
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}
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else {
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local maxrho=-2
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}
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*set trace on
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forvalues i=1/`nbpart' {
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forvalues j=1/`nbpart' {
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forvalues k=`first`i''/`last`i'' {
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forvalues l=`first`j''/`last`j'' {
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if `i'!=`j' {
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if `k'>`l' {
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local sumdiff=`sumdiff'+`Cov'[`k',`l']
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}
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if (`Cov'[`k',`l'])^`quad'>(`maxrho')^`quad' {
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local maxrho=(`Cov'[`k',`l'])
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}
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matrix `W'[`k',`l']=-(`W'[`k',`l'])
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}
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else if (`Cov'[`k',`l'])^`quad'<(`minrho')^`quad'&`k'!=`l' {
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local minrho=`Cov'[`k',`l']
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}
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if `i'==`j'&`k'>`l' {
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local summeme=`summeme'+`Cov'[`k',`l']
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}
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local C=`C'+`W'[`k',`l']
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local C1=`C1'+abs(`W'[`k',`l'])
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if `W'[`k',`l']>+0 {
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local ++C2
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}
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}
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}
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}
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}
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if `meme'!=0 {
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local summeme=`summeme'/`meme'
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}
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if `diff'!=0 {
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local sumdiff=`sumdiff'/`diff'
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}
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local diffsum=`summeme'-`sumdiff'
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set trace off
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di "Summeme: `summeme' ; Sumdiff: `sumdiff'"
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local minrho=(`minrho')^(`quad')
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local maxrho=(`maxrho')^(`quad')
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local C=sign(`C')*(abs(`C'))^(1/`quad')/(`nbvar'*(`nbvar'-1))+`mean'
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local C1=(`C1')^(1/`quad')/(`nbvar'*(`nbvar'-1))
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local C2=(`C2')/(`nbvar'*(`nbvar'-1))*100
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return local Pcov=`=`C'/`C1''
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return local Pel=`=`C2'/100'
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if `nbpart'==1 {
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local C=`C'*(`nbvar'+1)/`nbvar'
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}
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*di "C:" `C' " C1: " `C1' " C2: " `C2'
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if `nbpart'==1 {
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local maxrho=0
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}
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if `nbpart'==`nbvar' {
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local minrho=0
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}
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di " C=(`meme'*`minrho'-`diff'*`maxrho')/(`meme'+`diff')"
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local C=(`meme'*`minrho'-`diff'*`maxrho')/(`meme'+`diff')
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di in green "{hline 80}"
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di in green "Number of individuals: " _col(71) in ye %8.0f `nbind'
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di in green "Number of variables: " _col(71) in ye %8.0f `nbvar'
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di in green "COMPART index: " _col(71) in ye %8.6f `C'
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di in green "Proportion of the covariances explained by the COMPART index: " _col(73) in ye %6.2f `=abs(`C')/`C1'*100' "%"
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di in green "Proportion of positive elements in the matrix: " _col(73) in ye %6.2f `C2' "%"
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di in green "Minimum correlation coefficient for 2 variables of the same group: " _col(74) in ye %5.2f `minrho'
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di in green "Maximum correlation coefficient for 2 variables of two different groups: " _col(74) in ye %5.2f `maxrho'
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di in green "Average correlation coefficient: " _col(74) in ye %5.2f `mean'
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di in green "{hline 80}"
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di
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if "`details'"!="" {
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di in green "Matrix of the coefficients"
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di in green "{hline 26}"
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matrix list `W' ,noheader format(%7.4f)
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di
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}
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if "`variables'"!="" {
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di in green "Details for each variable"
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di in green "{hline 26}"
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di
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di in green "{hline 80}"
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di in green "Items" _col(17) "COMPART" _col(26) "Problematic items"
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di in green "{hline 80}"
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tempname Cvar
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matrix `Cvar'=J(1,`nbvar',0)
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forvalues i=1/`nbvar' {
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local C`i'=0
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local pourri`i'
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forvalues j=1/`nbvar' {
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local C`i'=`C`i''+`W'[`i',`j']
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if `W'[`i',`j']<0 {
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local pourri`i' `pourri`i'' ``j''
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}
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}
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local C`i'=`C`i''/(`nbvar'-1)
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matrix `Cvar'[1,`i']=`C`i''
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di in ye abbrev("``i''",14) _col(15) %9.6f `C`i'' _c
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if "`pourri`i''"!="" {
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di in ye _col(26) "`pourri`i''"
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}
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else {
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di
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}
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}
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di in green "{hline 80}"
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matrix colnames `Cvar'=`varlist'
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matrix rownames `Cvar'=Compart
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return matrix Cvar=`Cvar'
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}
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local test=`maxrho'-`minrho'
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local diffsum=(`summeme'*`meme'-`diff'*`sumdiff')/(`meme'+`diff')
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local diffsum=`summeme'/*-`sumdiff'*/
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return local compart `C'
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return local mean `mean'
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return local list `varlist'
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return local part `part'
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restore
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end
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