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Re: st: Constraint, Poisson, & pseudo R^2
I usually report one or two pseudo R^2 values as a standard practice and use
other methods to assess model fit. I was just surprised that version 7
reports a pseudo R^2 value whereas version 8 does not.
In a message dated 10/20/2004 7:58:08 AM Eastern Standard Time,
I do not have the entire answer, but I think I can narrow the problem
down a bit. The pseudo R^2 that -fitstat- report require the
loglikelihood of the model with only the constant, and -poisson- with
constraints do not report or save these. I do not know why. You could
of course estimate your model with only the constant and use the
formulas on page 92 of the long and freese book to calculate them
manually, but I would not do that before someone tells us why STATA
no longer reports these.
Why do you want to use the pseudo R^2? If you want to compare
constraint and unconstraint models, the likelihood ratio test is by
far more appropriate. If you want to asses model fit than I would
first test for overdispersion (for instance estimate a negative
binomial -nbreg- and test whether alpha equals zero) since this is
the most common problem with poisson regression.
--- In firstname.lastname@example.org, Rkaminski@a... wrote:
> Dave - thanks for your reply. I'm not using Scott's add on for
> estimation. Interestingly, Stata version 7 provides the pseudo-R^2
> using the constraint, but version 8 does not. This makes me think
> intentionally eliminated it from the output in the latest
> someone will know the reason why. Maybe it is not appropriate to
> R^2 value under these conditions?
> Bob Kaminski
> Dept. of Criminology & Criminal Justice
> University of South Carolina
> In a message dated 10/19/2004 1:50:37 PM Eastern Standard Time,
> jacobs.184@s... writes:
> That's almost certainly because Long and Freeze use their add on
> that calculates psuedo R squares. I can't remember the name of the
> program, but it is listed repeatedly in the Long and Freeze book.
> Dave Jacobs
> Ohio State
> At 08:00 AM 10/19/2004 -0400, you wrote:
> >In the Long & Freeze book published by Stata, the authors
> >regression model using the constraint command to control for
> >exposure. It produces the same coefficients as when using
> >offset, but
> >the pseudo-R^2 value is substantially larger when using the
> >(p. 265). However, when I use the constraint option, Stata does
> >produce a
> >pseudo-R^2 value. Does anyone know whether there has been a
change made to
> >the program by Stata?
> >Thanks in advance.
> >Bob Kaminski
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