Dear Statalist,

In Stata 14/15 in a GSEM model is it possible to obtain an estimate of the overall effect of an exogenous/independent variable on an "ultimate" endogenous/dependent variable when the path linking the exogenous variable and the ultimate endogenous variable goes via two separately linked endogenous variables, where the error/links of the endogenous variables may differ? I assume this is conceptually the same as the "total effect" in a standard mediation model? I know you can obtain total/direct/indirect effects in a GSEM model in Mplus, but it appears not in Stata's GSEM?

Here is a reproducible example of the form of model I am interested in, where the overall effect I am interested in is of "smoke" on "bwt_ord". Note the differing errors/links of the endogenous variables. My ultimate endogenous variable is ordinal, hence the (probably unnecessary) creation of an ordinal variable.

* Load data

webuse lbw, clear

* Create ordinal variable

gen bwt_ord = .

replace bwt_ord = 0 if (bwt <= 2500)

replace bwt_ord = 1 if (bwt > 2500 & bwt < 3500)

replace bwt_ord = 2 if (bwt > 3500)

* GSEM model

gsem (smoke -> ftv, family(poisson) link(log)) ///

(smoke -> age, family(gaussian) link(identity)) ///

(ftv -> bwt_ord, family(ordinal) link(logit)) ///

(age -> bwt_ord, family(ordinal) link(logit))

If there is no way to obtain estimates of "overall effect" parameters for the exogenous variable, are there any alternatives, e.g. in the model above predicting values of bwt_ord as values of smoke differ (with identical changes in all paths for smoke)?

Thank you

In Stata 14/15 in a GSEM model is it possible to obtain an estimate of the overall effect of an exogenous/independent variable on an "ultimate" endogenous/dependent variable when the path linking the exogenous variable and the ultimate endogenous variable goes via two separately linked endogenous variables, where the error/links of the endogenous variables may differ? I assume this is conceptually the same as the "total effect" in a standard mediation model? I know you can obtain total/direct/indirect effects in a GSEM model in Mplus, but it appears not in Stata's GSEM?

Here is a reproducible example of the form of model I am interested in, where the overall effect I am interested in is of "smoke" on "bwt_ord". Note the differing errors/links of the endogenous variables. My ultimate endogenous variable is ordinal, hence the (probably unnecessary) creation of an ordinal variable.

* Load data

webuse lbw, clear

* Create ordinal variable

gen bwt_ord = .

replace bwt_ord = 0 if (bwt <= 2500)

replace bwt_ord = 1 if (bwt > 2500 & bwt < 3500)

replace bwt_ord = 2 if (bwt > 3500)

* GSEM model

gsem (smoke -> ftv, family(poisson) link(log)) ///

(smoke -> age, family(gaussian) link(identity)) ///

(ftv -> bwt_ord, family(ordinal) link(logit)) ///

(age -> bwt_ord, family(ordinal) link(logit))

If there is no way to obtain estimates of "overall effect" parameters for the exogenous variable, are there any alternatives, e.g. in the model above predicting values of bwt_ord as values of smoke differ (with identical changes in all paths for smoke)?

Thank you

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