Longitudinal SEM and Latent Growth Curves

Hi everyone,

I am using OpenMx to fit a growth model with 2 continuous TICs. The results looked well; however, I noticed that the biases of path coefficients of the 2nd TIC were systematically larger than those of the 1st TIC in simulation studies. I am not sure if such patterns resulted from data generation, or from model misspecification, or from optimizer I used (the default one). I am attaching the script for one replication and the path diagram (with 6 repeated measures) of the model, any advice would be appreciated.

Does anyone have example path specification code to run a basic linear growth model where the slope and intercept factors are decomposed into ACE based on twin data? Thanks!

Hi all,

I am conducting simulation studies of LGC, and I found that the improper solution rates were pretty high in my model (If a solution with any variance of growth factor less than 0 or any correlation out of [-1, 1], I defined it as improper. Attached is the number of improper solutions out of 1000 replications). I am wondering when specifying an LGC in OpenMx, should I add constraints on variance or correlations? Or I can just exclude those improper solutions from simulation studies simply?

Thanks in advance!

Hi all,

I am conducting latent basis models and have got estimations. I want to plot the functional form of individuals. Is there any way for OpenMx to plot those y hat's for each individual automatically? Or at least can I have those y hat values directly?

Thank you in advance!

I'm interested in running a multiple group latent growth model to test for invariance in growth parameters across two groups, by constraining particular parameters to be equal across groups (vs freely estimating) and doing LL chi-square model comparisons.