Re: Alternate explanations

[Bernard L Cohen <blc+@pitt.edu>]

	I do treat the migration problem in my papers in what I consider
to be a plausible manner, and no one has previously challenged it.. With
the model proposed here, I would have to calculate the required
correlations with radon levels to check if they are implausible. This
would take some effort and time, and the results would not be
publishable.
	I therefore would like to change my reward offer to requiring that
the suggestion be submitted for publication as a "letter to the editor" or
in some other form. My response would then be publishable, which would
justify my time and effort.
	Do people think it is fair for me to make this modification in my
reward offer?

Bernard L. Cohen
Physics Dept.
University of Pittsburgh
Pittsburgh, PA 15260
Tel: (412)624-9245
Fax: (412)624-9163
e-mail: blc+@pitt.edu


On Tue, 3 Mar 1998, David Scherer wrote:

> Dr. Cohen has asked for a plausible, quantifiable explanation for his
> results.  If he allows the use of internal, confounding variables there
> would be numerous ways to do this.  I will illustrate the methodology with
> migration as such a confounder.
> 
> People who die in County A may have lived in any other county.  Thus for
> County A, the average radon dose is a linear combination of all counties in
> the data set.  Thus, (D a) = Sum-over-i (W ai * C i) where (D a) is the
> radon Dose for people who die in County A,  (W ai) are migration weighting
> factors, and (C i) are the radon concentration in County I.  
> Each (W ij) is the lifetime fraction of time spent in County J by people
> who die in Count I. This produces a large system of simultaneous linear
> equations.  I am confident that some set of Wai will result in a linear
> relationship between (Dose i) and  (M i), the smoking-corrected lung cancer
> mortality in County I.
> 
> Procedurally, you start with the (M i), and derive a set of doses (D i) =
> (risk) * (M i).  Here (risk) is the risk coefficient you want to use.  You
> plug these (D i) into the matrix equation above and sovle for the matrix
> elements (M ij).  However, you need to modify the smoking corrrection by
> the same set of (W ij).  Perhaps this could be solved simultaneously of
> iteratively.  The explanation is "plausible" if the diagonal elements are
> fairly large and the other elements are generally smaller as you move from
> further the main diagonal.
> 
> You could follow a similar procedure with other confounding variables
> (socioeconomic status, employment, family history, smoking, et cetera ad
> infinitum).  But they remain conjecture - these are not real, empirical
> data.  (The absence of these data is one weakness of the experimental
> design.)  It is obvious that this procedure will not produce any
> information about radon risk; it's a numbers game.  But, it does show that
> internal variables could offer other explanations for Dr. Cohen's results.
> 
> I have no interest in performing the calculation, and I waive any claim to
> the $5K bounty.
> 
> Regards,
> Dave Scherer
> scherer@uiuc.edu
>