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Hi Dr Muthen, I am reading the article : Muthen, B. (1998). Secondgeneration structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class/latent growth modeling. and at the same time I am learning from the imput and the output from Mplus web site. I would like to ask you few questions. From penn8, 1)How to get Table 10.3: Probality of dependence Given Class? For example, how to calculate P(Dep c=1) =.20 2)What is the meaning of : a) Intercepts C#1 2.461 0.311 7.906 0.000 C#2 3.379 0.595 5.681 0.000 b) What is the meaning of Category > 1 in LATENT CLASS ODDS RATIO RESULTS Latent Class 1 Compared to Latent Class 2 DEP94 Category > 1 0.548 0.218 2.510 0.012 Thank you in advance for your help. 


This is part of our Short Course material for the mixture days. Very briefly, 1) Probability = 1/ (1 + exp(Logit)) where Logit =  threshold. Odds = Probability/(1  Probability) Odds Ratio = Odds (class k)/Odds (class K) for K = 4 2a) Those are the intercepts in the latent class multinomial regression on covariates ("c on x")  see chapter 13 of the UG, 2b) Categories are 1, 2, 3... for polytomous outcomes. So 1 and 2 for binary outcomes. Therefore, with a binary outcome >1 means category 2. 


Hi Dr Muthen, Thank you for your answer it was very helpful. Today my question is about Local maxima in mixture modeling. What can we do with a local maximum problem. I have already incresed the number of starts (from 50 to 500), but I still have this message: WARNING: THE BEST LOGLIKELIHOOD VALUE WAS NOT REPLICATED. THE SOLUTION MAY NOT BE TRUSTWORTHY DUE TO LOCAL MAXIMA. INCREASE THE NUMBER OF RANDOM STARTS. Thank you in advance. 


You may need more random starts, for example, 5000 500. If increasing the random starts does not solve the problem, please send your input, data, output, and license number to support@statmodel.com. 

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