I am attempting to build a GMM in which there are 3 known classes and 2 latent classes per treatment group (decided based upon comparison of fit statistics and class sizes). Within each Class, I would like to fix intercepts to be common, but allow the slopes to be random. Intercepts can differ between each class.
I currently have: %CT#1.C#1% [i1]; [s1];
%CT#1.C#2% [i1]; [s1];
etc for CT#2 and CT#3
What do I need to add to my 'I1's to ensure that individuals within a class have common intercepts?
I would like the mean intercepts to be held equal for each latent class within its respective known class. Slopes can be random. That is, I would like the model to find individuals within, e.g. CT1.C1, that have a common intercept, but random slopes. This intercept should not be constrained to be equal to the intercept in, e.g. CT1.C2, CT2.C1, etc.
Would this produce those results: %CT#1.C#1% [i1] (1); [s1];