I have twelve binary latent class indicators to identifying my subgroups. I observed 3-class model fits the data well. I want to use gender "gend" as a measurement invariance to examine differences in the latent classes. Below is my model to accomplish the task.
I have few questions: 1. Is the model correct to accomplish the task?
2. Which is correct when using a restricted model to compare model indices where I constrained the parameters across groups (i.e., I will not include c ON cg in my model)?
classes = cg(2) c(3); vs. classes = c(3) cg(2);
Thank you and hope to hear from you! KB
............................... !Model 1: (Unrestricted model: All parameters allowed to vary across group)
... variable: names bk a b c d e f g h i j k l gend; usevariables = a-l; categorical = a-l; knownclass = cg(gend = 0 gend =1); classes = cg(2) c(3); missing = all(-999); cluster = bk; analysis: type = mixture complex; processor = 10; starts = 1000 50; model: %overall% c ON cg;