Published on *OpenMx* (http://openmx.psyc.virginia.edu)

By *dadrivr*

Created *09/26/2012 - 15:21*

Wed, 09/26/2012 - 15:21 — dadrivr [1]

I am trying to fit a longitudinal CFA with 3 indicators at each of 4 time points, with a 1 year time lag. The model runs fine when I have 3 time points, but the model fails when I add the fourth time point. It appears that the model may fail because of multicollinearity among the latent factors (the correlation between the latent factors at T3 and T4 = .996). I have already specified the within-indicator residual covariances across time, but it does not solve the problem. Here are the correlations of the 4 latent vars:

lag T=1: .988, .990, .996

lag T=2: .976, .967

lag T=3: .937

Any ideas for how to specify the longitudinal CFA given the high correlation among the latent variables across time? The 3 indicators represent questionnaires by three raters: mothers, teachers, and fathers.

Thanks in advance!

**Links:**

[1] http://openmx.psyc.virginia.edu/users/dadrivr

[2] http://openmx.psyc.virginia.edu/thread/1776

[3] http://openmx.psyc.virginia.edu/thread/1581

[4] http://openmx.psyc.virginia.edu/forums/opensem-forums/longitudinal-sem-and-latent-growth-curves