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 Dennis Li posted on Thursday, July 28, 2016 - 2:06 am
I am running an analysis with 8-10 binary milestone variables measured over 5 time periods. Once a milestone becomes 1, there's no transitioning backwards to 0. Also, the proportion of 1s starts high >80% for most milestones. Without adding covariates yet, I put all 50 variables into a RMLCA to see if it would run, and, to my surprise, the models converged. I was able to calculate VLMRLRT and BLRT for all models, and entropy values for k=1-5 were >.96, with fairly substantive interpretations.

However, for models k>2, I received a NON-POSITIVE DEFINITE FIRST-ORDER DERIVATIVE PRODUCT MATRIX error, with the issue being a threshold parameter and a small condition number. Scouring the message boards, I found an old discussion (URL copied below) in which Bengt says "Thresholds that go large like that are harmless causes of the non-pos def message" but also "You don't want a very small condition number and [-0.783D-15 in this case] is very small."

Should I just take that my models are non-identified and not even look at the results? Is it even a good idea to run multiple indicators with multiple time points in the same model? I am quite new to LCA and am stumbling with some of the basic ins and outs. Thanks.

The post I was referring to is:
 Bengt O. Muthen posted on Thursday, July 28, 2016 - 9:27 am
If you have very large thresholds that weren't fixed by Mplus, that can give you a small condition number. This is not necessarily harmful, however. Your model may well be identified.

A bigger issue is perhaps that your model does not reflect the no transitioning backwards from 1 to 0. That feature is characteristic of discrete-time survival analysis (although that is typically done for a single variable).
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