Respected Prof. Muthen. In my current project I have a panel data (variables collected over time) as follows: X variable named NP is for three time periods (Np_t1, NP_t2, NP_t3); Y variables named lnP is for four time periods (lnP_t1,lnP_t2,lnP_t3,lnP_t4) Two Moderator Z1, Z2 (interaction variables) are time-invariant As the focus is not in growth pattern of X or Y variable I am not using growth curve modeling. So I need to go for multilevel modeling of this data, in long format? However if I turn to long format, there is a challenge in the 'data structure' as X is only for three periods, Y is for four periods. So I kindly request your advice on how to model the equation: Y is function of (X, Z1, Z2, X*z1, X*z2) and to guide which format of the two is best; either using: 1.) wide format: but no need of growth pattern just account for the clustering of records within time like in multilevel 2.) OR using long format
When you do 2-level (long format) modeling you correlate different time points for the same individual, so that's what you mimic in the wide approach. The x's are correlated by default (not part of the model parameters) and you can correlate the y's in several ways, one being having residual correlations (y2-y4 WITH y2-y4). And add interactions at every time point if needed.
Then ask for Modindices and see what you've misspecified.