Re: st: Latent class estimation

[Laura Gibbons <gibbonsl@u.washington.edu>]

And the R package is -ltm-.  -Laura

On Wed, 5 Dec 2007, Christian Deindl wrote:

> to make the list complete: there is also a possibility in SAS to estimate LCA 
> models: PROC LCA.
> you can download it via the methodology center of pennstate university 
> (http://methcenter.psu.edu/)
>
> it is really nice and easy to handle.
>
>
> christian
>
> On Wed, 5 Dec 2007 12:45:26 -0500
> "Verkuilen, Jay" <JVerkuilen@gc.cuny.edu> wrote:
>
> > Phil Schumm wrote:
> >
> > > > > I would like to offer an alternative opinion.  RE references that are
> > accessible, Bartholomew's "Latent Variable Models and Factor  Analysis" 
> > (1987, Charles Griffin & Co.) offers a good theoretical  introduction, and 
> > Skrondal and Rabe-Hesketh's "Generalized Latent  Variable Modeling" (2005, 
> > Chapman & Hall) is superb in terms of both  its theoretical and applied 
> > presentation.  The latter should be read  in any case without question.<<<
> >
> > Bartholomew's book had a second edition (co-authored with Martin Knott).
> >
> >
> > There's also a Stata-specific book Multilevel and Longitudinal Modeling
> > Using Stata by Skrondal and Rabe-Hesketh. I would recommend seeing
> > http://www.gllamm.org for example code, the GLLAMM manual, etc. 
> >
> > > > > The program -gllamm- (type -ssc install gllamm-) is capable of 
> > estimating latent class models in a very flexible manner, and the  manual 
> > available with the program (as well as the book cited above)  offer several 
> > worked examples.  It can be slow for datasets with a  large number of 
> > unique covariate patterns, but this has to be  evaluated relative to the 
> > time required to learn how to use another  program and to move your data 
> > and results back and forth.  It's  certainly an excellent place to start 
> > and to run some preliminary  analyses; you can always then move to another 
> > piece of software if  speed becomes a problem.<<<
> >
> > Yeah, LatentGOLD, LEM, and Mplus would all be the ones I'd figure as
> > places to go if GLLAMM doesn't work out, or else coding things up in
> > software like winBUGS. There might be an R package of some sort that
> > does this; there are so many I can't possibly keep up with them all.
> >
> > IMO it is wise to do the analysis in multiple software packages---these
> > models are tricky. Mixture regression is particularly known for having
> > multiple optima problems and run the serious risk of capitalizing on
> > chance, especially in "exploratory" mode when there aren't covariates
> > predicting class membership or other things to constrain the model. 
> > Jay
> >
> > *
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> __________________
> Christian Deindl
> Universit�t Z�rich
> Soziologisches Institut
> Andreasstr. 15
> CH - 8050 Z�rich
> Tel: 044/635 23 46
> *
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Laura E. Gibbons, PhD
General Internal Medicine, University of Washington
Box 359780
Harborview Medical Center
325 Ninth Avenue, Seattle, WA  98104

phone: 206-744-1842   fax: 206-744-9917
Office address: 401 Broadway, Suite 5122
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