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Re: st: Transforming regressors prior to estimation in count models

From   Richard Williams <[email protected]>
To   [email protected]
Subject   Re: st: Transforming regressors prior to estimation in count models
Date   Tue, 07 Jun 2005 15:19:00 -0500

At 03:43 PM 6/7/2005 -0400, [email protected] wrote:
Dear All,

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 impression
that typically one begins with untransformed variables in count models, assess
the fit, and then -- if necessary -- transforms regressors.

Any thoughts on these approaches?
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.

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
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