*!plssem_p version 0.4.1
*!Written 17Feb2024
*!Written by Sergio Venturini and Mehmet Mehmetoglu
*!The following code is distributed under GNU General Public License version 3 (GPL-3)
program plssem_p, rclass sortpreserve
version 15.1
syntax , [ xb RESiduals NOOUTer NOINner ]
/* Options:
--------
xb --> fitted values
residuals --> residuals
noouter --> no results returned for the outer model
noinner --> no results returned for the inner model
*/
/* Description:
------------
This postestimation command computes fitted values and residuals for a
PLS-SEM model.
*/
tempvar __touse__
quietly generate `__touse__' = e(sample)
local ismi = (e(cmd) == "mi estimate")
if (`ismi') {
display as error "plssem postestimation is not available after multiple imputation"
exit
}
local tempnamelist
// check that estimation sample has not changed
// checkestimationsample
if ("`e(formative)'" != "") {
display as txt "(fitted values and residuals computed only " _continue
display as txt "for reflective latent variables)"
}
if ("`noinner'" != "") & ("`noouter'" != "") {
display as txt "noinner and noouter option chosen simultaneously; " _continue
display as txt "nothing saved"
}
else {
if ("`xb'" == "") & ("`residuals'" == "") {
display as txt "(option " _continue
display as result "xb" _continue
display as txt " assumed; fitted values)"
local xb "xb"
}
}
local refl = e(reflective)
local empty = .
local noreflective : list refl == empty
local props = e(properties)
local struct "structural"
local isstruct : list struct in props
if (!`isstruct') {
display as txt "(the model doesn't include any structural part; " _continue
display as txt "quantities saved only for the measurement part)"
}
local unscaled "unscaled"
local isunscaled : list unscaled in props
local knnimp "knn"
local isknnimp : list knnimp in props
local meanimp "mean"
local ismeanimp : list meanimp in props
if (`isknnimp') {
local missing "knn"
}
else if (`ismeanimp') {
local missing "mean"
}
else {
local missing ""
}
/* Save original data set */
local allindicators = e(mvs)
tempname original_data original_data_exp
local tempnamelist "`tempnamelist' `original_data' `original_data_exp'"
mata: `original_data' = st_data(., "`: list uniq allindicators'", "`__touse__'")
mata: `original_data_exp' = st_data(., "`allindicators'", "`__touse__'")
/* Recovery of missing values */
if ("`missing'" != "") {
mata: st_store(., tokens("`: list uniq allindicators'"), "`__touse__'", ///
st_matrix("e(imputed_data)"))
}
/* Save fitted values */
tempname latents
local lvs `e(lvs)'
mkmat `lvs' if `__touse__', matrix(`latents')
/* -- outer model -- */
if (!`noreflective') {
tempname adj_meas loadings b2use ohat modeA_scores indicators ///
indicators_std tmp
local modeA `e(reflective)'
local lvs_adj : colnames e(adj_meas)
matrix `adj_meas' = e(adj_meas)
matrix `loadings' = e(loadings)
local mvs : rownames `adj_meas'
local n_lvs : word count `modeA'
local n_mvs : word count `mvs'
mkmat `mvs' if `__touse__', matrix(`indicators')
mkmat `modeA' if `__touse__', matrix(`modeA_scores')
local idx = 1
local start = 1
quietly count if `__touse__'
local nobs = r(N)
mata: st_matrix("`ohat'", J(`nobs', 0, .))
tempname mvs_idx load_var load_idx load_nm num_block
local tempnamelist "`tempnamelist' `mvs_idx' `load_var' `load_idx' `load_nm' `num_block'"
mata: `mvs_idx' = J(0, 1, .)
foreach var in `modeA' {
local lv_col : list posof "`var'" in lvs_adj
mata: `load_var' = st_matrix("`loadings'")[., `lv_col']
mata: `load_idx' = selectindex(`load_var' :!= .)
mata: `mvs_idx' = (`mvs_idx' \ `load_idx')
mata: `load_nm' = st_matrixrowstripe("`loadings'")[`load_idx', .]
mata: `num_block' = rows(`load_idx')
mata: st_local("nblock", strofreal(`num_block'))
mata: st_matrix("`b2use'", transposeonly(`load_var'[`load_idx', .]))
mata: st_matrixcolstripe("`b2use'", `load_nm')
mata: st_matrix("`tmp'", ///
st_matrix("`modeA_scores'")[., `idx'] * st_matrix("`b2use'"))
mata: st_matrix("`ohat'", (st_matrix("`ohat'"), st_matrix("`tmp'")))
local ++idx
local end = `start' + `nblock' - 1
matrix `ohat'[1, `start'] = `tmp'
local start = `end' + 1
local tmp_nm = ""
forvalues j = 1/`nblock' {
local tmp_nm "`tmp_nm' `var'`: word `j' of `: colnames `b2use'''_hat"
}
local tmp_nm : list clean tmp_nm
local ohat_nm "`ohat_nm' `tmp_nm'"
}
local ohat_nm : list clean ohat_nm
matrix colnames `ohat' = `ohat_nm'
}
/* -- inner model -- */
if (`isstruct') {
tempname adj_struct path endo path_mata ihat lvs_endo_nm
local tempnamelist "`tempnamelist' `endo' `path_mata' `lvs_endo_nm'"
matrix `adj_struct' = e(adj_struct)
matrix `path' = e(pathcoef)
mata: `endo' = colsum(st_matrix("`adj_struct'"))
mata: `endo' = (`endo' :> 0)
mata: st_local("n_endo", strofreal(sum(`endo')))
mata: `path_mata' = st_matrix("`path'")[., selectindex(`endo')]
mata: st_matrix("`ihat'", st_matrix("`latents'") * `path_mata')
mata: `lvs_endo_nm' = st_matrixcolstripe("`path'")[selectindex(`endo'), 2]
forvalues j = 1/`n_endo' {
mata: st_local("lvs_endo", `lvs_endo_nm'[`j'])
local endovs "`endovs' `lvs_endo'"
local ihat_nm "`ihat_nm' `lvs_endo'_hat"
}
local ihat_nm : list clean ihat_nm
matrix colnames `ihat' = `ihat_nm'
}
/* End of saving fitted values */
/* Save residuals */
/* -- outer model -- */
if (!`noreflective') {
tempname ores mvs_nm
local tempnamelist "`tempnamelist' `mvs_nm'"
if (!`isunscaled') {
mata: st_matrix("`indicators_std'", ///
scale(st_matrix("`indicators'")[., `mvs_idx']))
matrix `ores' = `indicators_std' - `ohat'
}
else {
matrix `ores' = `indicators' - `ohat'
}
mata: `mvs_nm' = st_matrixcolstripe("`indicators'")[`mvs_idx', 2]
mata: st_local("n_ind", strofreal(rows(`mvs_idx')))
forvalues j = 1/`n_ind' {
mata: st_local("ind_nm", `mvs_nm'[`j'])
local indvs "`indvs' `ind_nm'"
}
local ores_nm : subinstr local ohat_nm "_hat" "_res", all
matrix colnames `ores' = `ores_nm'
}
/* -- inner model -- */
if (`isstruct') {
tempname ires
mata: st_matrix("`latents'", st_matrix("`latents'")[., selectindex(`endo')])
matrix `ires' = `latents' - `ihat'
forvalues j = 1/`n_endo' {
mata: st_local("lvs_endo", `lvs_endo_nm'[`j'])
local ires_nm "`ires_nm' `lvs_endo'_res"
}
matrix colnames `ires' = `ires_nm'
}
/* End of saving residuals */
/*
/* All fitted values */
tempname yhat
if (!`noreflective') & (`isstruct') {
matrix `yhat' = (`ohat', `ihat')
matrix colnames `yhat' = `ohat_nm' `ihat_nm'
}
else if (!`noreflective') & (!`isstruct') {
matrix `yhat' = `ohat'
matrix colnames `yhat' = `ohat_nm'
}
else if (`noreflective') & (`isstruct') {
matrix `yhat' = `ihat'
matrix colnames `yhat' = `ihat_nm'
}
else {
// nothing to save
}
/* All residuals */
tempname res
if (!`noreflective') & (`isstruct') {
matrix `res' = (`ores', `ires')
matrix colnames `res' = `ores_nm' `ires_nm'
}
else if (!`noreflective') & (!`isstruct') {
matrix `res' = `ores'
matrix colnames `res' = `ores_nm'
}
else if (`noreflective') & (`isstruct') {
matrix `res' = `ires'
matrix colnames `res' = `ires_nm'
}
else {
// nothing to save
}
*/
/* Copy quantities in data set */
local now "`c(current_date)', `c(current_time)'"
local now : list clean now
if ("`xb'" != "") {
if ("`noouter'" == "") & (!`noreflective') {
forvalues j = 1/`n_ind' {
local varname "`: word `j' of `ohat_nm''"
capture confirm new variable `varname'
if (_rc == 110) {
quietly drop `varname'
}
quietly generate double `varname' = .
label variable `varname' "Fitted values for outer model (`: word `j' of `indvs'') [`now']"
}
tempname ohat_mata orig_m orig_s
local tempnamelist "`tempnamelist' `ohat_mata' `orig_m' `orig_s'"
mata: `ohat_mata' = st_matrix("`ohat'")
mata: `orig_m' = mean(`original_data_exp')[`mvs_idx']
mata: `orig_s' = sd(`original_data_exp')[`mvs_idx']
mata: st_matrix("`ohat'", unscale(scale(`ohat_mata'), `orig_s', `orig_m'))
mata: st_store(., tokens("`ohat_nm'"), "`__touse__'", st_matrix("`ohat'"))
}
if ("`noinner'" == "") & (`isstruct') {
forvalues j = 1/`n_endo' {
local varname "`: word `j' of `ihat_nm''"
capture confirm new variable `varname'
if (_rc == 110) {
quietly drop `varname'
}
quietly generate double `varname' = .
label variable `varname' "Fitted values for inner model (`: word `j' of `endovs'') [`now']"
}
mata: st_store(., tokens("`ihat_nm'"), "`__touse__'", st_matrix("`ihat'"))
}
}
if ("`residuals'" != "") {
if ("`noouter'" == "") & (!`noreflective') {
forvalues j = 1/`n_ind' {
local varname "`: word `j' of `ores_nm''"
capture confirm new variable `varname'
if (_rc == 110) {
quietly drop `varname'
}
quietly generate double `varname' = .
label variable `varname' "Residuals for outer model (`: word `j' of `indvs'') [`now']"
}
mata: st_store(., tokens("`ores_nm'"), "`__touse__'", st_matrix("`ores'"))
}
if ("`noinner'" == "") & (`isstruct') {
forvalues j = 1/`n_endo' {
local varname "`: word `j' of `ires_nm''"
capture confirm new variable `varname'
if (_rc == 110) {
quietly drop `varname'
}
quietly generate double `varname' = .
label variable `varname' "Residuals for inner model (`: word `j' of `endovs'') [`now']"
}
mata: st_store(., tokens("`ires_nm'"), "`__touse__'", st_matrix("`ires'"))
}
}
/* End of copying quantities in data set */
/* Clean up */
if ("`missing'" != "") {
mata: st_store(., tokens("`: list uniq allindicators'"), "`__touse__'", ///
`original_data')
}
capture mata: cleanup(st_local("tempnamelist"))
/* End of cleaning up */
/* Return values */
if (!`noreflective') | (`isstruct') {
return matrix struct_res = `ires'
return matrix meas_res = `ores'
return matrix struct_fit = `ihat'
return matrix meas_fit = `ohat'
}
/* End of returning */
end