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

 From Kristian Karlson To statalist@hsphsun2.harvard.edu Subject Re: st: Conditional expectations for each latent class with gllapred Date Thu, 30 Dec 2010 17:47:01 +0100

```Stas,

Thanks. My bad with the datafile. It is

webuse union, clear
sample 25
gllamm union age grade year, i(idcode) ip(f) nip(2) l(logit) f(binom)

```
After quite some googling, I learned that -gllapred- option -us()- may be the right thing for me. I came to that conclusion by reading http://www.stata.com/meeting/2nasug/lclass.pdf, not the helpfile (which I find a bit difficult to understand, at least the -us()- option). I will also look into your suggestion about manipulating -gllapred- using option -from()-.
```
Thanks.

Kristian

Den 30-12-2010 16:37, Stas Kolenikov skrev:
```
```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.
```
```

. 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
```*