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Jan Ivanouw posted on Thursday, June 05, 2008 - 7:29 am
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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)? |
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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. |
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Thank you for the clarification Jan Ivanouw |
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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. |
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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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