Hello all,
I am utilizing gsem in Stata 18.0 for a latent class analysis with multiply imputed data and survey weights.
After I run my LCA, I am unable to get goodness of fit stats, receiving the error message "estat lcgof not valid." See my sample code for an example.
I asked if there was a solution to this on another thread, but I got no response, so now I am trying to calculate the BIC on my own. To do so, I need to know what the log likelihood is for my model.
So, my question is this: how can I determine the log likelihood for my model in order to calculate the BIC?
Or, alternatively, is there another way to go about this?
Thank you!
Note: I realize that it is difficult to answer some questions without sample data. Due to the restricted status of my data and complexity of this analysis, I am unable to do so.
I am utilizing gsem in Stata 18.0 for a latent class analysis with multiply imputed data and survey weights.
After I run my LCA, I am unable to get goodness of fit stats, receiving the error message "estat lcgof not valid." See my sample code for an example.
Code:
mi est, cmdok:gsem (var1 var2 var3 var4 var5 <-) [pweight= gsw5] , logit lclass(c 2) estat lcgof estat lcgof is not valid
So, my question is this: how can I determine the log likelihood for my model in order to calculate the BIC?
Or, alternatively, is there another way to go about this?
Thank you!
Note: I realize that it is difficult to answer some questions without sample data. Due to the restricted status of my data and complexity of this analysis, I am unable to do so.

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