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re: st: weights in xtlogit


From   "Airey, David C" <david.airey@Vanderbilt.Edu>
To   Statalist <statalist@hsphsun2.harvard.edu>
Subject   re: st: weights in xtlogit
Date   Mon, 16 Nov 2009 20:21:49 -0600

Thanks Austin and Stas!

That is good to know. I prefer your first practical approach for simulation, and the xtlogit for modeling the real data.

-Dave

> If you have 1000 obs per cluster, you might prefer to include fixed
> effects (50 or so dummies) in regular logit--the bias from using
> dummies is quite small when the number of obs per cluster is large.
> Also, if you have 50-60 clusters (20-30 per T/C group rather than
> 20-30 in both groups) you can use the cluster-robust VCE.  The bias
> (in SEs) is quite small with more than 50 balanced clusters.  This
> should be fairly easy to simulate, since -logit- is fast.  A better
> simulation would compare to -xtlogit- of course, but 10000 iterations
> of something that takes a day to converge is not feasible... though if
> you supply the true parameter vector with option from(b), it might
> converge a bit faster.



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