RE: Cohen's Ecologic Studies

[BERNARD L COHEN <blc+@PITT.EDU>]

On Tue, 4 Jun 2002 epirad@mchsi.com wrote:



> Dr. Cohen,

>

> To ignore non-linearity is the root cause of your

> findings.



	--Linearity of confounding factors has no relevance to my study



 In an ecologic analysis you are limited to a

> summary statistics to adjust for confounding.  Since you

> do not have information on covariates at the county

> level, accurate ratio functions cannot be calculated.



	--Why can't you make up a specific numerical example?





> This becomes very problematic if the data structure is

> non linear (e.g. not everyone in the county smokes

> cigarettes for the same duration and intensity; not

> everyone spends the same amount of time in their home,

> not everyone is exposed to the same radon concentration,

> etc...), and non additive, which is the case at hand.



	--Why can't you make up a specific numerical example and show how

it can affect my results?



>

> I believe the onus is on you to show that multiple non-

> linear covariates are not the cause of your problem.

> The only way I know you can attempt to do this is use

> the methods of Sheppard and colleagues.

>



	--I never assume anything is linear, except lung cancer vs radon.

I need a numerical example to understand what you are talking about.



> Lubin has demonstrated the problem in a recent paper

> just using smoking.



	--My papers give examples of how errors in smoking can explain my

results, but then I show that the required correlations are completely

implausible. Lubin never addresses the issue of plausibility.



 Your inverse associations are found

> for other smoking related cancers that should not be

> related to radon.  This further strengthens my argument

> that your inability to adjust adequately for smoking is

> driving your findings.  Or do you believe the reason the

> other smoking related cancers also have an inverse

> association with your radon concentrations is because of

> a hormetic response due to alpha radiation exposure to

> the lung?



	--I have addressed this in previous messages



 I find it far more credible that the

> explanation is lack of control of confounding by smoking

> and other factors as Lubin has just demonstrated.

>

	--In BEIR-IV, smoking is not a confounder. Smokers and non-smokers

are treated as entirely different species.





> You 1997a) claim that simple linear least squares

> regression of m on S indicates that nearly all lung

> cancer is due to smoking.  However, the results of this

> analysis do not support such a claim.  We repeated the

> regression of lung cancer mortality rates on your

> adjusted smoking percentages.  The resulting R2 values

> indicated that S explains only 23.7% of the variation in

> lung cancer mortality rates among females and 34.5%

> among males.  Puntoni et al. (1995) compared six

> mathematical models relating cigarette smoking to lung

> cancer risk using data from nine large cohort studies.

> They found that 67% of the variation in relative risks

> could be explained by a two-stage model of

> carcinogenesis.  In comparison, very few of the lung

> cancer deaths are explained by your smoking variable.

> Therefore, the smoking variable is inadequate to adjust

> for the effects of smoking.

>

	--I have addressed the R-squared issue previously and shown that

it is irrelevant

	--I have also shown that any choices of the smoking prevalences in

the various counties that are not completely implausible would not affect my results.



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