Re: st: margin and gsem

[Klaus Pforr <kpforr@googlemail.com>]

Thank you very much for clearing that up!

Klaus

Am 26.08.2013 23:31, schrieb Jeff Pitblado, StataCorp LP:
> Klaus Pforr <kpforr@googlemail.com> is using -margins- after -gsem-, but
> -margins- is not returning estimable results when it should:
>
> > I used some of the examples and tried to estimate margins of responses
> > and marginal effects. So far I could not manage to get estimate from
> > margin with any of the gsem examples.
> >
> > I'm especially interested in multilevel mlogit models. I am fully
> > aware of the problems with the random part with this problem, but the
> > predict(fixedonly) option did not help in any way.
> >
> > Just to give an idea, what I am talking about, I put in some examples:
> >
> > * This is an mlogit. The problem does not change, when you run a logit
> > on only two outcomes
> > use http://www.stata-press.com/data/r13/gsem_lineup
> > gsem (i.chosen <- i.location i.suswhite i.witmale i.violent
> > M1[suspect]@1), mlogit
> > margin, predict(mu fixedonly)
> > margin, dydx(*) predict(mu fixedonly)
> >
> > * This is a linear model. The problem does not change, when you break
> > the continous variable in
> > * groups and run logit or mlogit
> > use "http://www.stata-press.com/data/r13/gsem_fifeschool";, clear
> > gsem (attain <- vrq i.sex M1[pid] M2[sid]),
> > margin, predict(mu fixedonly)
> > margin, dydx(*) predict(mu fixedonly)
> >
> > Has anyone worked with an gsem example, in which margins worked?
> Klaus has found a bug in how -margins- handles -gsem- results containing
> multilevel latent variables.
>
> -margins- is mistakenly treating multilevel latent variables (e.g.
> M1[suspect]) as intercepts, which is causing it to fail the estimable
> functions test.
>
> The fix for this should be available in the next update to Stata 13.
>
> --Jeff
> jpitblado@stata.com
> *
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--
__________________________________
Dr. Klaus Pforr
GESIS -- Leibniz Institut für Sozialwissenschaft
B2,1
Postfach 122155
D - 68072 Mannheim
Tel: +49 621 1246 298
Fax: +49 621 1246 100
E-Mail: klaus.pforr@gesis.org
__________________________________

*
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