I am trying to estimate a parallel process latent growth model with five waves of data from adolescence to early adulthood. The outcomes are depression (continuous) and number of conduct disorder symptoms (count, maximum 4). The sample size is 662. My input is:
Thanks - I have already tried each growth model separately, and they run fine and make sense.
I tried your montecarlo suggestion, but still fail to get estimates, and the following error message:
THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY DUE TO A NON-ZERO DERIVATIVE OF THE OBSERVED-DATA LOGLIKELIHOOD.
THE MCONVERGENCE CRITERION OF THE EM ALGORITHM IS NOT FULFILLED. CHECK YOUR STARTING VALUES OR INCREASE THE NUMBER OF MITERATIONS. ESTIMATES CANNOT BE TRUSTED. THE LOGLIKELIHOOD DERIVATIVE FOR PARAMETER 17 IS -0.66093711D+01.
Is it possible that the data are simply not suitable for this type of model?