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Re: st: Conditional expectations for each latent class with gllapred


From   Partha Deb <partha.deb@hunter.cuny.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Conditional expectations for each latent class with gllapred
Date   Thu, 30 Dec 2010 12:21:02 -0500

Stas and Kristian,

-fmm- does not support models for binomial outcomes because finite mixture distributions are not generally identified for binary outcomes. The setup in -glamm- imposes restrictions as Stas points out - only the intercept varies across classes and thus is, in principle identified (although if one estimated a model with no X variables, even this would not be identified). -fmm- estimates "unconstrained" mixtures by default, so I chose not to include models for binomial outcomes.

Hope this helps.

Happy New Year to all.

cheers.

Partha

On 12/30/2010 10:37 AM, Stas Kolenikov wrote:
On Thu, Dec 30, 2010 at 3:06 AM, Kristian Karlson
<kristian.karlson@gmail.com>  wrote:
I have run the following -gllamm- model in Stata. It is a finite mixture
binary logit model with two latent classes:

use http://www.ats.ucla.edu/stat/paperexamples/singer/hsb12.dta, clear
sample 25
gllamm union age grade year, i(idcode) ip(f) nip(2) l(logit) f(binom)

I am interested in the conditional expectation for latent class: Pr(Union =
1 | u_1) and Pr(Union = 1 | u_2), where u_1 is latent class 1 and u_2 is
latent class 2.

I have looked at -gllapred-, but haven't been able to compute these. My idea
was to use options mu and marg, but these probabilities are the mixed
probabilities, not the ones from each component.
Your example does not run:

. gllamm union age grade year, i(idcode) ip(f) nip(2) l(logit) f(binom)
variable union not found
r(111);

You probably meant a different data set.

Note that this is a pretty restrictive model in which the effects of
the predictors are kept constant across classes, and the difference is
only via a shift.

You might be able to manipulate -gllapred- using -from()- option. For
that, you can create two matrices with the estimated point masses and
their weights fixed to one and the other class. Just a suggestion, I
never worked with mixture models using -gllamm-.

Your other option is to use -fmm- package that might provide
additional flexibility if it supports -logit- link (or an analogue
of).


--
Partha Deb
Professor of Economics
Director of Graduate Studies
Hunter College
ph:  (212) 772-5435
fax: (212) 772-5398
http://urban.hunter.cuny.edu/~deb/

Emancipate yourselves from mental slavery
None but ourselves can free our minds.
	- Bob Marley

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