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From | "Christian Deindl" <deindl@soziologie.uzh.ch> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: Latent class estimation |
Date | Wed, 05 Dec 2007 20:29:32 +0100 |
Phil Schumm wrote: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.<<<I would like to offer an alternative opinion. RE references that are
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.
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.<<<The program -gllamm- (type -ssc install gllamm-) is capable of
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 * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/
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