We collected mental health data on 4 continents and want to examine the invariance of 5 separate measures with a sample size of 1000. One obstacle that I've run into is that running the analysis with all 5 measures at once leads to more parameters than people, and I get a warning that the model is not positive definite. I've tried running it with fixed and it did not resolve the problem.
Would it make sense to run separate alignment analyses for each of the 5 measures? When I try this, the problem seems to be resolved.
Also, is there a method to use the values from alignment analysis for future analyses? We want to see how each measure below (P, D, R, S, and A) relates to a few other outcome variables.