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 Brian Don posted on Monday, November 11, 2013 - 8:31 pm
I am working on a latent class growth analysis with 4 waves of data. For class 1, the intercept, slope, and quadratic terms were significant, while for the 2nd class only the intercept was significant. When running conditional analyses, I have regressed the predictors only onto the slope and intercept of the 2nd class (as seen in the following syntax), because of the fixed quadratic term.

%OVERALL%
i s q| AnxM1@0 AnxM2@3 AnxM3@6 AnxM4@11;
i-q@0;
c on sexf Dep SE;
%c#1%
[i s q];
i s q on sexf Dep SE;
%c#2%
[i s q@0];
i s on sexf Dep SE;

Is this the correct procedure for running conditional analyses when one class has a significant quadratic term but the other does not? Thanks in advance for your help.
 Bengt O. Muthen posted on Tuesday, November 12, 2013 - 2:34 am
You can do it this way, but it is fine to keep the quadratic slope in the second class - when adding predictors of it, it might have significant slopes, which would mean it varies (due to more power for instance).
 Brian Don posted on Tuesday, November 19, 2013 - 4:01 pm
Thanks very much for your help. One last question: I've been having problems with the classes switching when I attempt to fix the quadratic component for class 2. This occurred in a previous analysis about a year ago, and I was instructed by Linda to use the STARTS = 0 command and use starting values drawn from the unconditional model. So, I used the following syntax and just wanted to be sure this was correct:

ANALYSIS: TYPE = COMPLEX MIXTURE;
Starts = 0;

MODEL:
%OVERALL%
i s q | AnxM1@0 AnxM2@3 AnxM3@6 AnxM4@11;
i-q@0;
c on sexf Dep SE Psup RAS_full;
%c#1%
[i*0.396 s*-0.048 q*0.003];
i s q on sexf Dep SE Psup RAS_full;
%c#2%
[i*1.038 s*-0.037 q@0];
i s on sexf Dep SE Psup RAS_full;
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