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Jan Ivanouw posted on Wednesday, March 21, 2012  10:15 am



I am wondering how the class probabilities are calculated in a mixed model (with no covariates, in order to keep things simple). In part 2 in the paper Lübke and Muthén "Investigating population heterogeneity with factor mixed models" (2005) it is mentioned that class probabilities are calculated using multinomial regression. Is this a different approch for calculating class probability than in a LCA (without any latent continuous factor), and which terms are used in this multinomial regression? In the paper is also mentioned A as a parameter describing how class membership influences eta. Is this A the same as the parameter Alpha (C) given in the Mplus output from a mixed model? 


In a model with no covariates, there is no multinomial regression. See the class proportions in the results. Class membership influencing a factor is seen in the factor means varying across classes. 

Jan Ivanouw posted on Wednesday, April 04, 2012  12:22 pm



Thank you. What I wonder is this: Class probabilities for a LCAmodel are calculated as described in appendix 8 of the Technical appendices. It seems, though, that this method does not work quite the same way with FMMmodel (of type FMM2 in Clark, Muthen et al.  branch 1 of the paper Muthén, 2008 Latent variable hybrids) I would like to ask how are class probabilities calculated for the FMMmodel? 


There are no explicit formulas for this as numerical integration is required. The following paper which is available on the website might help: Muthén, B. & Asparouhov, T. (2009). Growth mixture modeling: Analysis with nonGaussian random effects. In Fitzmaurice, G., Davidian, M., Verbeke, G. & Molenberghs, G. (eds.), Longitudinal Data Analysis, pp. 143165. Boca Raton: Chapman & Hall/CRC Press. 

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