I missed the previous post you are referring to but why not use -xtnbreg- if
you know you have overdispersion in your data?
Carter Rees
School of Criminal Justice
University at Albany, SUNY
[email protected]
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Scott Cunningham
Sent: Tuesday, September 12, 2006 8:13 AM
To: [email protected]
Subject: st: poisson - bootstrapping or clustering?
I'm estimating a model of sexual partners using -xtpoisson- and -
poisson-. The data suffers from overdispersion, and so I'm trying to
correct for that using bootstrapping within -xtpoisson-. But as I
posted the other day, I'm having trouble recovering the marginal
effects in post-estimation. I have a memory of someone telling me
that the cluster() option within -poisson- can correct for
overdispersion. Does anyone with experience in count data have
recommendations? This is micro-level data from the National
Longitudinal Survey of Youth (1997). The problem with -mfx, dydx-
appears to be that bootstrapping within -xtpoisson- had numerous
failures in calculating the standard errors. That's at least what I
think is going wrong.
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