Jon Heron posted on Wednesday, July 25, 2012 - 4:33 am
I am attempting to fit second order growth models to two processes in parallel with directional associations between the various growth factors.
Say I have first order factors:- b1 b2 b3 b4 b5 b6, a1 a2 a3 a4 a5 a6 and second order factors:- aint aslope aquad bint bslope bquad
This model is stretching both me and my PC (mainly me) so I am currently contemplating a two-stage approach where I fit a simpler model that covaries all my first order factors (ai,bi). I then read the tech4 output back into Mplus and fit the parallel growth model to these vars/covs/means.
I have a feeling this approach may have some shortcomings but is still useful/valid for informing a full one-stage model -e.g. in terms of my chosen polynomials and res-variance constraints.
Does this sound reasonable or am I missing something?
Dear Dr.Muthen; You explained about "Multiple indicator linear growth model for continuous Outcomes" and "Two-level growth model for a continuous outcome (three-level analysis)" in example 6.14 and 9.12, respectively in your excellent user's guide. Can we run multilevel multiple-indicator linear growth model in Mplus? Please introduce me a reference about that?? Thanks a lot. Mahdi
But when I used MLR method, the model did not converge and this warning is appeared:
WARNING: THE LATENT VARIABLE COVARIANCE MATRIX (PSI) IS NOT POSITIVE DEFINITE. THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR A LATENT VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO LATENT VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO LATENT VARIABLES. CHECK THE TECH4 OUTPUT FOR MORE INFORMATION.
THE H1 MODEL ESTIMATION DID NOT CONVERGE. SAMPLE STATISTICS COULD NOT BE COMPUTED. INCREASE THE NUMBER OF H1ITERATIONS.