More than one categorical latent in LCA PreviousNext
Mplus Discussion > Latent Variable Mixture Modeling >
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 Dipali Rinker posted on Sunday, September 08, 2013 - 4:15 pm
Hello, do you have any resources for interpreting the Mplus output for more than one categorical latent? I have already looked at example 7.14 in the manual. Thank you.
 Bengt O. Muthen posted on Sunday, September 08, 2013 - 8:10 pm
Look under Papers, Latent Class Analysis on our website. For instance, I think the Feingold paper has this flavor. Then there is of course the Latent Transition Analysis literature.
 Georg Datler posted on Tuesday, November 12, 2013 - 9:48 am
Can Mplus also perform "EXPLORATORY latent class factor analysis" (well, the term used by Magidson & Vermunt 2001)?

If yes, how would Ex. 7.14 have to be altered?

Many thanks!
 Linda K. Muthen posted on Tuesday, November 12, 2013 - 12:12 pm
I think this is our TYPE = MISTURE EFA. See Example 4.4.
 Georg Datler posted on Wednesday, November 13, 2013 - 4:09 am
Thank you!
I would like to explore how many categorical latent variables ("factors") are necessary to grasp the pattern in a set of dichotomous observed variables.
(.i.e. there would be no continous latent variable as in Ex 4.4.)

Magidson & Vermunt call it the "latent class factor approach"
Vermunt, J. K., and Magidson, J. (2001), Latent class factor and cluster models, bi-plots and related graphical displays, Sociological Methodology, 31, 223264.
 Bengt O. Muthen posted on Thursday, November 14, 2013 - 8:26 am
I think that means using several latent class variables. The UG has examples of LCA with several latent class variables. So with 2 such variables you have e.g.

Model c1:

[different observed-variable means/thresholds for different c1 classes];

Model c2:

[different observed-variable means/thresholds for different c2 classes];

I think the special feature here is that for both Model c1 and Model c2 the observed-variable means/thresholds are given for all the observed variables to make the analysis exploratory.

Depending on your theory, c1 and c2 can be uncorrelated (default) or specified to correlate.
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