The sample size is 69. I obtained a reasonable grouping of the two groups (29/40) with very nice interpretation of the mean values of the two groups. The loglikelihood is about -151.383.
Now I re-ran the exactly same code with Mplus 3, because the code automatically searches the starting values of the largest loglikelihood, it chose the starting value with the loglikelihood at about -127.675 and continued. But this time the algorithm does not have a valid Fisher information matrix.
I also tried a simplified Mplus 3 code as following (no class specific starting values): MODEL: %OVERALL%
c#1 ON educ; It seems that Mplus cannot choose from the ten random trials for a good Fisher Information matrix and ask for user-supplied starting values.
I would like to know if my old results with smaller loglikelihood are qualified as MLE through Mplus 2. For the improvement of the loglikelihood, should I choose the larger loglikelihood with bad Fisher information or stay with the old results? Thanks.
This question should addressed to firstname.lastname@example.org. Please send both outputs, data, and your license number. Some defaults have changed between Version 2 and Version 3. This is likely the cause but we can determine exactly what is happening if we can have the above information.