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Re: Re: Risks of low level radiation - New Scientist Article





On Thu, 13 Dec 2001, John Williams wrote:



>

> It remains unclear to me how Cohen’s ecological data can be used to

> test LNT

> (or any other predictive theory). Cohen states that “…case-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” (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’s work does not test for a causal

> relationship, how can his data be a test for LNT (or any other

> predictive

> theory)?



	--LNT is a particular type of a causal relationship. My work

tests that particular type. A case-control study can determine any type

of causal relationship.



> Cohen goes on to say “We have…never claimed that low level exposure

> to radon

> is protective against lung cancer” (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-3)? Cohen cannot have it both ways.



	--I miss your logic here. A test can show that some particular

theory fails without determining what the correct theory is. For example,

one can test Newton's theory F = ma by measuring distance travelled vs.

time. But if there is friction so that the theory does not check out, one

could not determine the correct relationship (unless he did other

experiments in which there is no friction)



> Cohen quotes Richard Feynman in support of his test of LNT. According

> to

> Feynman “we 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 …observation, 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.” (Health Physics, Volume 72(4), page 624, April 1997).

> Implied in

> Feynman’s 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.



	--If my data were not valid, that would explain everything; in

fact for some years, I thought that was the explanation. But I kept

getting more data, and the results did not change. Then I got the EPA data

which was completely independent of mine, and the results were the same.

Before that, I got data for various individual states, including excellent

studies by Florida and New Jersey, and they agreed with my results for

those states. With all of this, it is hard to understand how the data

could be wrong. I am very open to suggestions on this.

	--I offered to do a new study with any ground rules or oversight

that anyone wanted to impose, for a modest cost, but no one was

interested.

	--Note that my results are the same if we consider only one

section of the country, or if we select counties on any other basis.







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