Richard,
I reestimated their models using the same variables with the same
transformed variables (some logs, some other transforms), but with a slightly expanded
set of observations in a different time period. I find no evidence of an
effect of their key regressor. I then thought I should do what you suggest, i.e.,
"start over" without assuming the regressors need to be or should be
transformed (at least initially).
I wasn't sure if there was a "rule of thumb" regarding whether one should
transform prior to estimation or whether one should wait until an assessment of
model fit suggests a need to do so. I also wasn't sure if there was a
difference between count models and OLS regarding assumptions of the RHS variables.
But thank you (and the others) for the responses so far. They are helpful.
Bob
In a message dated 6/7/2005 4:54:16 P.M. Eastern Standard Time,
[email protected] writes:
At 04:33 PM 6/7/2005 -0400, [email protected] wrote:
>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
Given that it is a replication, you probably have to do the same things
they did - but that doesn't mean that you can't eventually argue that a
non-transformation or an alternative transformation is better. It may also
become obvious early on why they did what they did.
It seems odd to me that they offer no rationale for the transformations,
but maybe the substance of the problem is such that it is just taken for
granted that things should be done this way.
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
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WWW (personal): http://www.nd.edu/~rwilliam
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