#delim ; prog def marglmean, rclass; version 14.0; /* Estimate marginal log mean (scenario log mean) from existing estimation results assumed to contain parameters of a model whose predicted values are positive conditional arithmetic means. *! Author: Roger Newson *! Date: 03 September 2015 */ syntax [if] [in] [pweight aweight fweight iweight], [ , Level(cilevel) post * ]; if "`post'"=="" {; tempname oldest; cap estimates store `oldest'; }; * Create estimation results *; _marglmean `if' `in' [`weight'`exp'] , `options' level(`level'); * Copy e() results to r() *; return scalar level=`level'; local mscalars: e(scalars); local nmscalar: word count `mscalars'; forv i1=`nmscalar'(-1)1 {; tempname ms_`i1'; local ename: word `i1' of `mscalars'; scal `ms_`i1''=e(`ename'); if !missing(`ms_`i1'') {; return scalar `ename'=`ms_`i1''; }; }; tempname btemp Vtemp; matr def `btemp'=e(b); matr def `Vtemp'=e(V); return matrix V=`Vtemp'; return matrix b=`btemp'; return local atspec `"`e(atspec)'"'; if "`post'"=="" {; cap estimates restore `oldest'; }; end; prog def _marglmean, eclass; version 14.0; /* Estimate marginal log mean (scenario log mean) from existing estimation results assumed to contain parameters of a model whose predicted values are positive conditional arithmetic means. */ * Find last estimation command *; local cmd "`e(cmd)'"; if `"`cmd'"'=="" {;error 301;}; local options "EForm Level(cilevel)"; if "`cmd'"=="marglmean" {; * Replay old estimation results *; syntax [, `options']; }; else {; * Create new estimation results *; syntax [if] [in] [pweight aweight fweight iweight], [ ATspec(string asis) `options' subpop(passthru) PRedict(passthru) vce(passthru) df(passthru) noEsample force ITERate(passthru) ]; * Assign default atspec() option and check that it returns only 1 scenario *; foreach AO in atspec {; cap _ms_at_parse ``AO'', asobserved; if _rc {; disp _n as error `"Invalid at-specification - `AO'(``AO'')"'; error 498; }; else {; cap conf matrix r(at); if !_rc {; local AOrows=rowsof(r(at)); if `AOrows'>1 {; disp _n as error `"Option `AO'(``AO'') returns `AOrows' scenarios"' _n "Only 1 scenario allowed"; error 498; }; if `"``AO''"'=="" {; local `AO' "(asobserved) _all"; }; }; }; }; marksample touse; qui margins if `touse' [`weight'`exp'], at(`atspec') `subpop' `predict' `vce' `df' `esample' `force' post; * Collect scalar e-results from margins *; local mscalars: e(scalars); local i1=0; foreach ename in `mscalars' {; local i1=`i1'+1; tempname ms_`i1'; scal `ms_`i1''=e(`ename'); }; qui nlcom ("Scenario_1":log(_b[_cons])), `iterate' `df' post; * Post scalar e-results from margins *; local nmscalar: word count `mscalars'; forv i1=`nmscalar'(-1)1 {; local ename: word `i1' of `mscalars'; if !missing(`ms_`i1'') {; ereturn scalar `ename'=`ms_`i1''; }; }; * Post local e-results *; ereturn local atspec `"`atspec'"'; ereturn local predict "marglmean_p"; ereturn local cmdline `""'; ereturn local cmd "marglmean"; }; * Display estimation results *; if "`eform'"!="" {; local eformopt "eform(Mean)"; disp as text "Scenario 1: " as result `"`atspec'"' _n as text "Asymmetric confidence interval for the marginal mean" _n "under Scenario 1"; }; else {; disp as text "Scenario 1: " as result `"`atspec'"' _n as text "Symmetric confidence interval for the log marginal mean" _n "under Scenario 1"; }; disp as text "Total number of observations used: " as result e(N); ereturn display, `eformopt' level(`level'); end;