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Mplus Discussion > Latent Variable Mixture Modeling >
 Jan Ivanouw posted on Thursday, June 05, 2008 - 7:29 am
Please, I am wondering about the following:

What is the difference between Latent Class Analysis and the old method 'cluster analysis' (which for instance is implemented in SPSS)?
 Linda K. Muthen posted on Thursday, June 05, 2008 - 7:58 am
LCA is a type of cluster analysis but not the same as what is in SPSS. See Chapter 3 of the following book:

Hagenaars and McCutcheon (2002). Applied Latent Class Analysis.
 Jan Ivanouw posted on Sunday, June 08, 2008 - 3:33 am
Thank you for the clarification

Jan Ivanouw
 Ana Maria Vedes Pacheco posted on Friday, March 15, 2013 - 4:25 pm
Dear Mrs. Muthen,

I have a dyadic data set (N=157 couples) and I have two main goals:

1) create a profile, separately, for females and males based on 6 continuous variables.

2) see how these profiles predict several continuous outcomes.

For 1) I tried:

a) two step cluster analysis and latent class analysis. The results of the cluster analysis were more sound.
So I have 2 clusters for females and males. To
answer goal 2) i would like to insert the clusters as predictors of my independent variables.
And finally test a mediation model inserting a continuous variable.

I wonder how can I do this analysis?
Is this a path analysis with categorical variables as predictors? If yes, where can I find an example of Mplus input.

Thank you in advance.
 Bengt O. Muthen posted on Friday, March 15, 2013 - 4:40 pm
Using the latent classes in the modeling is like doing multiple-group analysis. Eacb group/class can have its own parameters such as means, intercepts and regression slopes.

Note that you don't say "y ON c". Instead, this implies that the y means vary across the c classes.

So, the Mplus setup is straightforward. In addition to your latent class indicators you add the variables in your regression relationships and let those variable parameters vary across the classes.
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