Re: The Puskin Paper on radon and smoking

[Kai Kaletsch <eic@shaw.ca>]

Thanks for your quick response. It will take a while for me to digest this.



Kai



----- Original Message ----- 

From: "BERNARD L COHEN" <blc+@pitt.edu>

To: "Kai Kaletsch" <eic@shaw.ca>

Cc: "RadSafe" <radsafe@list.vanderbilt.edu>

Sent: Thursday, June 12, 2003 10:56 AM

Subject: Re: The Puskin Paper on radon and smoking





> >

> > Cohen's Response:

>

> > Cohen also offers a "test" of the Puskin hypothesis (and I don't agree

with

> > it). It goes like this:

> >

> > Cohen admits that there is a negative correlation between radon

> > concentration and smoking, but claims that the correlation is not strong

> > enough to account for the excess lung cancers found in low radon areas.

>

> --Puskin claims that the explanation of his observation is that my

> smoking data are erroneous, missing a strong negative correlation between

> smoking prevalence, S, and radon exposure, r. I show that there is no

> possible set of S-values that will lessen the problem posed by the Puskin

> observation.

>

> > He goes on to say that, even if he ordered the counties according to

smoking

> > prevalence and assumed a perfect negative correlation with the average

radon

> > concentration, that would not be sufficient to explain the negative

> > correlation between average radon concentration and lung cancer. In

other

> > words, there is not that much difference in smoking prevalence between

> > counties to explain the differences in lung cancer, regardless if the

low

> > radon counties happen to be at the top or the bottom of the smoking

scale.

>

> --With the Puskin type analysis,  differences in S-values between

> counties does not matter. The results listed in the column headed

> "Corr(S-r)=-1.0" in Table 1 of Item #7 on my web site show that there is

> no indication that the dependence of cancer rate on radon exposure is more

> positive for lung cancer than for the other smoking related cancers; if

> anything, the contrary seems to be the case, so the Puskin hypothesis

> (strong negative S-r correlation) does nothing to explain the Puskin

> observation.  The results in that column are independent of the width of

> the S- distribution. For example, if this width is doubled, the values in

> that column remain unchanged. I also consider changing the shape of the

> S-distribution, and this does not help.

>

> >

> > This does not make any sense to me: Either you have good smoking data,

then

> > your ranking will be pretty good and you don't have to reorder the

> counties,

> > or your data is bad and then your ranking may or may not be correct, but

the

> > width of the distribution is certainly biased toward the null. Consider

the

> > following example:

> >

> --I can understand your puzzlement about the fact that the width

> of the S-distribution does not matter. In my original treatment, I show

> that it does matter, but that the width required to explain the data is

> highly implausible. However, in the Puskin treatment, S and r are treated

> as independent variables in a multivariate regression, and for reasons I

> don't understand, values in the column labelled "Corr(S,r)=-1.0" are

> independent of the width.

> To check on this, I used two uniform distributions of S-values,

> one ranging from 90-110, and the other ranging from 70-130, three times as

> wide.With a perfect negative correlation with radon in each case, the

> values in the column labelled "Corr(S,r)=1.0" are the same.

>

>

> > There are two counties. County 1 has 100% non-smokers and county 2 has

100%

> > smokers. You decide to determine smoking status by asking everyone to

> > complete a survey. Half of everyone in each county does a good job

filling

> > out your survey. The other half randomly checks off yes or no, without

> > reading your question. Your survey will then show county 1 has 75%

> > non-smokers and 25% smokers while county 2 has 75% smokers and 25%

> > non-smokers. Your ranking is still correct (county 1 has more

non-smokers)

> > but the measured width of your distribution is only half of the correct

> > width. The true width of the distribution might be enough to account for

> > differences in lung cancer incidence, while the measured width might not

be.

>

> --See my above discussion showing that, in the Puskin analysis,

> the width does not matter.

>

> > Cohen also explains the sources of his smoking data and points out that

all

> > 3 independent methods of estimating smoking produce similar results. To

me,

> > that is more convincing than the reordering "test". It is also

impressive

> > that no one has yet proposed a reasonable smoking distribution, which

would

> > make Cohen's results compatible with LNT.

> >

> > Conclusion:

> >

> > I hope that more people follow Puskin's example and offer new input into

the

> > debate. Far too few people are involved in the scientific part of the

radon

> > debate. (There are plenty of people on the standard setting side of the

> > debate.)

> >

> > I hope that no one (including the NCRP) will consider the findings of

the

> > NCRP or any other group as final, until the theory is shown to be

compatible

> > with the data. I have no problem with NCRP or ICRP recommendations being

> > used for setting standards, however. After all, the purpose of

committees is

> > not to do any science, but rather to build consensus by applying

reasonable

> > and conservative principles. (Remember what the RP stands for!). They

are on

> > the standard setting side of the debate.

> >

> > Kai

> > http://www.eic.nu

> >

> >

>



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