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

 From Partha Deb 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)
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
of).

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

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None but ourselves can free our minds.
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