Re: st: Latent class estimation

[Dimitris Pavlopoulos <Dimitris.Pavlopoulos@soc.kuleuven.be>]

Dear Eva,

I have not explored the potential of STATA in latent class models, but  
I would suggest you to do your analysis in Latent Gold instead. This  
is a program especially made for such analysis. And yes, you need to  
use the EM algorithm and in particular its modified version (Baum  
Weltch algorithm or something like that). This is implemented in  
Latent Gold.

best,
Dimitris



Quoting Eva Poen <eva.poen@gmail.com>:


> Dear all,
>
> I am interested in running a latent class regression model. I need to
> estimate the class-specific regression models for the outcome variable
> y (with covariates x) and the coefficients for the class prediction
> equation (with covariates z). Before I can embark on such a project in
> Stata, I need to do some more reading though. The standard
> econometrics textbooks are silent on the matter of latent classes, and
> it is unclear to me how the likelihood function is constructed. If
> someone could recommend a good book/article detailing this method,
> that would be great.
>
> My specific questions are:
> - Do I need to use the EM algorithm, or can I use standard maximum   
> likelihood?
> - Can a latent class model accommodate cross-sectional time series data?
> - Can the sets of covariates x and z be overlapping?
> - Can x contain lagged values of y? Do I need to use instruments for those?
> - Can I have clustered data within the latent classes?  (standard
> errors adjusted for clustering, as in standard Stata regression
> commands -cluster(...)- )
>
>
> I'd be very grateful for any hints.
> Thanks a lot,
> Eva
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