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st: RE: Improvement in the goodness of fit and correctly predicted counts with IPF
From
"Martin Weiss" <[email protected]>
To
<[email protected]>
Subject
st: RE: Improvement in the goodness of fit and correctly predicted counts with IPF
Date
Fri, 9 Apr 2010 20:55:59 +0200
<>
" As far as I've learnt, log-linear models may be run with three different
STATA commands: IPF, GLM and POISSON"
Two FAQ violations in one sentence: Do not capitalize Stata, and let others
know that of your three commands, the first is a user-written contribution,
while the rest is part of official Stata.
HTH
Martin
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Luis Ortiz
Sent: Freitag, 9. April 2010 19:34
To: [email protected]
Subject: st: Improvement in the goodness of fit and correctly predicted
counts with IPF
Dear Statalisters,
As far as I've learnt, log-linear models may be run with three different
STATA commands: IPF, GLM and POISSON
The two latter ones provide a richer output, but I'm finding the computation
time too long. so that I do not have other option but to rely on the more
simple command IPF. In principle, it just provides the goodness of fit of
the model.
Does any one of you knows if there is any way of directly getting the
improvement in the goodness of fit, relative to a prior model, as well as
the proportion of cases correctly predicted by the model with IPF?
Many thanks in advance
Luis
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