st: After non-convergence with xtmixed

[Clyde Schechter <cschecht@aecom.yu.edu>]

When estimating a model with xtmixed, if the gradient-based 
optimization fails to converge (as is painfully often the case!), 
Stata reports results based only on the iterated EM 
optimization.  Why is that?  Despite non-convergence, the log 
restricted-likelihood at the point where gradient-based optimization 
quits is, in my experience, typically substantially higher than what 
prevailed at the end of iterated EM.  So why not report the results 
of the incomplete gradient-based calculations instead?  Is there some 
reason to believe that when the gradient-based method fails it 
actually provides worse estimates?  Or is it simply a matter of the 
details of programming that prevents that?

If the incomplete gradient based results are, as I'm inclined to 
believe, better than the final EM iteration, is there any option or 
work-around that will make Stata report them?  After all, those 
calculations sometimes represent many hours of extra calculation, and 
they seem to just go to waste.

Clyde Schechter
Associate Professor of Family & Social Medicine
Albert Einstein College of Medicine
Bronx, NY, USA


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