I'm trying to fit a parallel process latent growth curve model with a latent moderator as a predictor of one of the slopes. The latent moderator is the intercept multiplied by a latent variable (measured at time one). Basically, this is what I've asked of the model:
slopeY on interceptX;
slopeY on latentvariable; (main effect)
interaction | interceptX XWITH latentvariable;
slopeY on interaction; (interaction effect)
I get this error message: THE ESTIMATED COVARIANCE MATRIX COULD NOT BE INVERTED.COMPUTATION COULD NOT BE COMPLETED IN ITERATION 16.CHANGE YOUR MODEL AND/OR STARTING VALUES.
THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY DUE TO AN ERROR IN THE COMPUTATION. CHANGE YOUR MODEL AND/OR STARTING VALUES.
I'm wondering if it's possible to create this kind of interaction (latent variable X latent intercept)? Any help, advice, suggestions appreciated.
Thank you Dr. Muthen. I appreciate your advice. I was correlating the residuals across each process at each time point, but it seems there was another model specification error that I was missing until now. The model is running normally now. Thank you.