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Mplus Discussion > Growth Modeling of Longitudinal Data >
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 Anonymous posted on Monday, June 06, 2005 - 2:54 pm
Two years ago I ran the following code with Mplus 2:
MODEL:
%OVERALL%

c#1 ON educ;

f1 by madher1-madher6@1;

f2 by madher1@-2.5 madher2@-1.5 madher3@-.5 madher4@.5
madher5@1.5 madher6@2.5;

f3 by madher1@6.25 madher2@2.25 madher3-madher4@.25
madher5@2.25 madher6@6.25;

[madher1-madher6@0];

%c#1%

[f1*-0.03409 f2*0.00019 f3*0.000403];

%c#2%

[f1*-0.3461 f2*0.03901 f3*0.05065];

OUTPUT: tech8;

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%

f1 f2 f3 | madher1@0 madher2@1 madher3@2 madher4@3 madher5@4 madher6@5;

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.
 Linda K. Muthen posted on Monday, June 06, 2005 - 3:36 pm
This question should addressed to support@statmodel.com. 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.
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