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Re: Cohen's ecological data: a test of LNT?
Ken Mossman wrote:
>
> <P><FONT FACE=3D"Times New Roman">It remains unclear to me how =
> Cohen=92s ecological data can be used to test LNT (or any other =
> predictive theory).
--That is explained in my 1995 paper in Health Physics. Briefly,
LNT (for individuals) is used to derive mathematically a relationship
between county lung cancer rates and average radon exposures in those
counties. Data are provided for these, and these data show that the
predicted relationship is not fulfilled.
Cohen states that =93=85case-control studies =
> investigate the causal relationship between radon exposure and lung =
> cancer, whereas our work has the much more limited objective of testing =
> the linear no-threshold theory=94 (Health Physics, Volume 72(4), page =
> 625, April 1997). It is absurd to suggest that testing the LNT theory =
> is not a test of a causal relationship. The LNT theory, in this =
> context, only has meaning if radiation causes cancer. If Cohen=92s work =
> does not test for a causal relationship, how can his data be a test for =
> LNT (or any other predictive theory)? </FONT></P>
>
--LNT is a special case of a causal relationship. It is clearly
possible to have a causal relationship without having a linear-no
threshold (LNT) relationship. For example, there could be a quadratic, a
threshold, etc. My study tests LNT as a special case of the causal
relationship; it finds that LNT fails that test, grossly exaggerating the
risk from low level radiation. That is as far as I can interpret my data.
> <P><FONT FACE=3D"Times New Roman">Cohen goes on to say =93We =
> have=85never claimed that low level exposure to radon is protective =
> against lung cancer=94 (Health Physics, Volume 72(4), page 625, April =
> 1997). If the data refute LNT then what do the data support if not =
> hormesis (as suggested by the strong negative correlation for radon =
> concentrations <150 Bqm<SUP>-3</SUP>)? Cohen cannot have it both =
> ways.</FONT></P>
--I fail to follow the logic here. I am not able to use my data to
determine the dose-response relationship for individuals. To do so would
fall into the trap of "the ecological fallacy". All my data do show is
that LNT (for individuals) grossly exaggerates the risk from low level
radiation. That conclusion avoids "the ecological fallacy".
Why is it "having it both ways" to conclude that LNT is wrong, but
my data cannot determine what is right?
>
> <P><FONT FACE=3D"Times New Roman">Cohen quotes Richard Feynman in =
> support of his test of LNT. According to Feynman =93we look for a new =
> law by the following process: first we guess at it. Then we compute the =
> consequences of the guess to see what would be implied if this law we =
> guessed is right. Then we compare the result of the computation with =
> =85observation, to see if it works. If it disagrees with experiment =
> [the law] is wrong. In that simple statement is the key to science. It =
> does not make any difference how beautiful your guess is. It does not =
> make any difference how smart you are, who made the guess, or what his =
> name is-if it disagrees with experiment it is wrong. That is all there =
> is to it.=94 (Health Physics, Volume 72(4), page 624, April 1997). =
> Implied in Feynman=92s statement is that the data provide a bona fide =
> test of the theory. If the data are erroneous (e.g., use of faulty data =
> analysis, use of inappropriate statistical tests, use of inappropriate =
> experimental methods) then the data do not provide a test of the theory =
> even though the data, on its face, might suggest the theory is wrong. =
> </FONT></P>
>
--Obviously if the data or the analyses are faulty, any
conclusions from it are unreliable. Therefore the discussion should be
about what might be wrong with the data or the analyses. I have been
searching for possible problems for many years without finding anything,
and that is why I am offering rewards for help in this search.
>
Bernard L. Cohen
Physics Dept.
University of Pittsburgh
Pittsburgh, PA 15260
Tel: (412)624-9245
Fax: (412)624-9163
e-mail: blc+@pitt.edu
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