Carter and Richard,
Let me clarify that they were estimating count models (not OLS), and that a
rationale for why they started with transformed variables was not given
(theoretical or otherwise).
Bob
In a message dated 6/7/2005 4:24:57 P.M. Eastern Standard Time,
[email protected] writes:
Bob,
Was their model also a count model or did they transform to meet the
normality assumption of OLS?
Carter
------------------------------------------------------------------------------
----------------------
In a message dated 6/7/2005 4:19:56 P.M. Eastern Standard Time,
[email protected]_ (mailto:[email protected]) writes:
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.
-----Original Message-----
From: [email protected] [mailto:[email protected]]
Sent: Tuesday, June 07, 2005 1:44 PM
To: [email protected]
Subject: st: Transforming regressors prior to estimation in count models
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?
Thanks in advance.
Bob Kaminski
Department of Criminology and Criminal Justice
Currell College
University of South Carolina
[email protected]
(803) 777-1560
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/