Good morning. I ran a LGM analysis with type=missing and estimation used ML. However, the model sample size seemed to include all of the covariates in addition to the six repeated measures. I wrote Linda on this list and she (you) suggested I use type=missing random to use all available data on the y variable. This worked, however I noticed that the estimator is MLR. What is the reason for this?
I ran the model with ML estimation and the results were slightly different (i.e., one effect that was significant at p=.05 is now significant at (p<.05). Is this problematic? Can I simply use ML instead of MLR to stay consistent?