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Re: st: Transforming regressors prior to estimation in count models
At 03:43 PM 6/7/2005 -0400, Rkaminski@aol.com wrote:
First off, I'm not aware of anything "special" about count models when it
comes to transformations of the regressors, e.g. I don't know why your
strategy would inherently be different for count models than, say, for
OLS. But, there are lots of things I am not aware of, so maybe somebody
can offer more insights on this.
I'm about to embark on an analysis using count models to replicate a study
in which the authors log transformed or used some other transformation on
their regressors prior to estimating their models. I was under the
that typically one begins with untransformed variables in count models,
the fit, and then -- if necessary -- transforms regressors.
Any thoughts on these approaches?
In general, it seems to me that variable transformations are driven by
theoretical and/or empirical concerns. Theory might argue that you should
take logs, squares or whatever; and if theory is ambivalent or silent then
observed empirical relationships may guide the choice.
If you are in the theory is silent category - then I would probably proceed
as you say. There are all sorts of ways to transform variables, so I don't
think I would try them all out just to see what happens. But, if you are
replicating someone else's work, they may have had good reasons for doing
what they did, so theory may not be silent here.
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
WWW (personal): http://www.nd.edu/~rwilliam
WWW (department): http://www.nd.edu/~soc
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