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 Jennifer Rose posted on Monday, July 16, 2007 - 8:36 am
Hi,

I'm running a GMM specifying 2-4 classes on a continuous outcome for 4 time points. The 2 class model runs without a problem, but the 3 class model gives me a warning that the latent variable covariance matrix is not positive definite. Based on a preliminary LGC analysis including a quadratic slope, I specified the slope coefficients as fixed in the GMM. What is interesting is that when I run a 4 class model, it runs without a problem (i.e., normal convergence and no warnings). Do you have any suggestions for why this might happen for a 3 class model, but not a 4 class model? Are the fit indices (e.g., BIC) and the test for k-1 classes trustworthy when you get a warning like this?

Thanks in advance,
Jen Rose
 Linda K. Muthen posted on Monday, July 16, 2007 - 10:16 am
If you get such a warning, the results should not be interpreted. If you send your input, data, output, and license number to support@statmodel.com, I can take a look at it.
 Yoon Oh posted on Monday, April 29, 2019 - 1:32 pm
Hi,

I was running Growth Mixture Models with up to 7 classes. All models with 2-4 classes and 6-7 classes ran without any problem, but only the model with 5 classes encountered the following warning message. Would you please help me how to address this problem? Thank you. -- Yoon

THE STANDARD ERRORS OF THE MODEL PARAMETER ESTIMATES MAY NOT BE
TRUSTWORTHY FOR SOME PARAMETERS DUE TO A NON-POSITIVE DEFINITE
FIRST-ORDER DERIVATIVE PRODUCT MATRIX. THIS MAY BE DUE TO THE STARTING
VALUES BUT MAY ALSO BE AN INDICATION OF MODEL NONIDENTIFICATION. THE
CONDITION NUMBER IS 0.754D-11. PROBLEM INVOLVING THE FOLLOWING PARAMETER:
Parameter 20, %G#4%: [ Q ]
 Bengt O. Muthen posted on Tuesday, April 30, 2019 - 3:57 pm
We need to see your full output - send to Support along with your license number.
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