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st: After non-convergence with xtmixed

From   Clyde Schechter <[email protected]>
To   [email protected]
Subject   st: After non-convergence with xtmixed
Date   Wed, 02 Jan 2008 08:59:48 -0500

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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