2. It is the final value that the EM algorithm ends with. However this is not an identified parameter. Use the output option H1SE to determine what parameters are identifiable. You should get an entry of 999 for non-identified parameters in the "STANDARD ERRORS FOR H1 ESTIMATED SAMPLE STATISTICS" section.
yang posted on Thursday, September 08, 2011 - 2:21 pm
Thanks for your response. Just wanna make sure I got it...
1. By FIML I mean maximizing likelihood computed from individual data...not the Wishart likelihood computed via the covariance matrix which is produced by EM algorithm. Is that correct?
2. The EM algorithm you're talking about is only for estimating covariance matrix in the presence of missing data (i.e. if I delete SAMPSTAT from the input file, the algorithm won't be invoked)...not for estimating the model that I specify in the MODEL statement. Is that correct?