I know how to do multilevel growth modeling with time unstructured data and an "observed" dependent variable. I have a new dataset, however, where the DV is made up of several observed variables at each time point (the same observed variables at each point), is time unstructured and has 2 levels (3 if you count the occasions nested in individuals). I have a feeling that it is right under my nose, but I don't know "the name" of this analysis and where to start reading about it. I imagine it is "Latent Growth Curve Analysis" but I dont know where to look if I want understand the time unstructured and multilevel aspects. Any suggested readings or can anyone tell me the particular "name of this?" Thanks a bunch.
Yes, after reading example 9.15. This seems correct - a multiple indicator growth model. But to be sure allow me to describe how it is that my "Time" variable is (un)structured. The nature of the individually-varying times of observations is something like this:
Will this still work?? In most chapters on latent change analysis I have read, one way to test "slopes" is to respectively fix the parameters going from the latent "slope" variable to its indicators to 0,1,2,3 (etc). But with the time unstructured nature of my data this seems inappropriate (?). Thanks a bunch.