I am using BSEM with zero mean, small variance priors for correlating residuals in a longitudinal measurement invariance analysis. I noticed that I can either estimate residuals for each measurement occasion while ignoring residuals across time (i.e. constraining these to zero), or I can estimate all possible residuals. However, when I tried to estimate all residuals within each time-point + only residuals for the same items across time while constraining all other residuals across time to zero, I got the following error message:
*** FATAL ERROR THE VARIANCE COVARIANCE MATRIX IS NOT SUPPORTED. ONLY FULL VARIANCE COVARIANCE BLOCKS ARE ALLOWED. USE ALGORITHM=GIBBS(RW) TO RESOLVE THIS PROBLEM.
What is the reason for this? I can understand if I had to estimate all possible correlations or none at all, but it seems fine to estimate only the ones from the same measurement occasion. Can Mplus really know that the variables from the same occasion are related?
Ok, thanks for explaining. Can you recommend a good reference for reading about the Gibbs(RW) algorithm? I get other error messages when I try to switch to Gibbs(RW), so I guess I need to know more about this.