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?