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Re: st: Transformed values in logistic regression


From   Tim Wade <wade_tj@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Transformed values in logistic regression
Date   Fri, 27 Aug 2004 06:15:32 -0700 (PDT)

--- Ricardo Ovaldia <ovaldia@yahoo.com> wrote:

> Dear all,
> 
> Please pardon this non-Stata question, but I have
> not
> found a satisfactory resolution. 
> 
> We recently submitted a manuscript for publication
> and
> received a favorable reply, except that one of the
> reviewers criticized a transformation that we
> performed on a continuous variable prior to fitting
> a
> logistic regression model. 
> 
> Specifically we were interested in modeling
> case-control status as a function of several patient
> covariates including serum creatinine which in our
> data ranges from 0.11 to 1.98.
> Because of skewness and to make the odds ratio
> independent of the units measurement, we decided to
> log-transform the creatinine values before entering
> them into our logistic model. However the reviewer
> wrote “Using a log-transform for creatine is absurd
> because a 1-unit increase in ln(x) is equivalent to
> increasing x by a factor of 2.718 which is in the
> realm of impossibility”
> 
Ricardo, I think the reviewer might be partially
correct because a 1 ln increase is beyond the range of
the data, the coefficient associated with such an
increase in creatinine would be large and possibly
misleading. You could simply use "lincom
0.1*creatinine" to rescale the coefficient/odds ratio
to a more meaningful unit increase.

Tim


> Is he correct?  Isn’t the coefficient estimated such
> that the predicted values are within the range of
> the
> data and this only a problem if you attempt to
> extrapolate beyond the data range? What I am
> missing?
> 
> Thank you very much,
> Ricardo.   
> 
> 

=====
wade_tj@yahoo.com


		
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