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Hello, I want to compute a latent class analysis with nominal indicators (example 7.7 in the user's guide). I expected that for the values of the indicators conditional probabilities would be provided. Instead in the result section means are reported. How can a nominal variable have a mean? What mistake do I make? Does Mplus not make the same analysis like Latent Gold for example? Regards Christopher Hautmann 


The estimated item parameters that are reported are logits for the different categories of each nominal indicator. These logits can be translated into probabilities very easily using the multinomial logistic regression expression  this is discussed in Chapter 13 of the User's Guide. 

Ali posted on Tuesday, October 04, 2016  8:17 am



I run LCA with 4 nominal indicators and each indicator has 3 categories. But, I am no sure if I get the conditional probabilities for each indicator correctly. From the model results, there were means for each category in each latent class. For example, in the latent class 1, means for ST53Q01#1 is 1.080 ,and ST53Q01#2 is 1.753, but ST53Q01#3 was fixed as reference group . So, log odds (ST53Q01#1C=1)=1.08, log odds (ST53Q01#2C=1)=1.753, and log odds (ST53Q01#3C=1)=0 in Class 1. And,each log odds is exponentiated and summed. To get the conditional probability for each category in is that each expoentiated value is divide by the sum. Is it the correct procedure? 


Check how it is done in the UG chapter 14. See the multinomial logistic regression example with covariates all = 0. 

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