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Re: Cohen's latest reward
Don,
Your reference below deals with problems that arise when you try to take an
observation at the county level and make inferences about risk at an
individual level. The question still remains: What are the COUNTIES with
high radon doing right, to make them have low lung cancer mortality?
At the COUNTY level (considering counties, not individuals), Dr. Cohen's
data presents a cohort study with much better data than any of the miner
studies ever had. (One measurement per mine every few years or so and then
drawing 50% error bars - give me a break!)
An insurance company would be justified in offering lower life insurance
premiums to people living in counties with high radon, based on Dr.Cohen's
(or the EPA's) data. This has nothing to with whether one agrees with Dr.
Cohen's conclusion that the data is proof that LNT fails.
Kai
----- Original Message -----
From: "Rad health" <healthrad@HOTMAIL.COM>
To: <info@eic.nu>; <radsafe@list.vanderbilt.edu>
Sent: Wednesday, January 16, 2002 11:16 PM
Subject: Re: Cohen's latest reward
> Kai,
>
> Cross-level bias or inter and intra county variability are not a problem
for
> case-control studies since you have data from INDIVIDUALs or individual
> level data. As far as its plausibility, see:
>
> Ann Public Health 1995;16:61-81
>
> Ecologic studies in epidemiology: concepts, principles, and methods.
>
> Morgenstern H.
>
> Department of Epidemiology, University of California, Los Angeles, School
of
> Public Health, USA.
>
> An ecologic study focuses on the comparison of groups, rather than
> individuals; thus, individual-level data are missing on the joint
> distribution of variables within groups. Variables in an ecologic analysis
> may be aggregate measures, environmental measures, or global measures. The
> purpose of an ecologic analysis may be to make biologic inferences about
> effects on individual risks or to make ecologic inferences about effects
on
> group rates. Ecologic study designs may be classified on two dimensions:
(a)
> whether the primary group is measured (exploratory vs analytic study); and
> (b) whether subjects are grouped by place (multiple-group study), by time
> (time-trend study), or by place and time (mixed study). Despite several
> practical advantages of ecologic studies, there are many methodologic
> problems that severely limit causal inference, including ecologic and
> cross-level bias, problems of confounder control, within-group
> misclassification, lack of adequate data, temporal ambiguity,
collinearity,
> and migration across groups.
>
> ----------------------------
>
>
> Don Smith
>
>
> >From: Kai Kaletsch <info@eic.nu>
> >
> >Don,
> >
> >"inter county variability" in itself can never be a reason for anything,
> >not
> >just Cohen's data. There has to be a systematic reason (mechanism) why
> >inter
> >county variability would produce such a strong correlation. If there is
> >random inter county variability, it would bias the results toward the
null.
> >
> >If you have a graph of x vs. y which shows a statistically significant
> >structure, your explanation of the graph must, in some way, involve both
x
> >and y. Otherwise it is not an explanation of the graph. This holds for
all
> >sciences. Epidemiology is not exempt from the basic laws of logic.
> >
> >Kai Kaletsch
> >
> >P.S.: You can probably control the inter county variability (by
stratifying
> >the data) better than you can control the inter person variability (by
> >choosing the right controls) in case control studies. Would you not be
more
> >concerned about "intra" county variability? As long as you leave the data
> >at
> >the county level, there is no ecological fallacy. You could consider each
> >county to be an organism [my version of the Gaia theory :) ]. You would
> >still be left with the question: What are the counties with high radon
> >doing
> >right and what are the counties with low radon doing wrong?
> >
> >----- Original Message -----
> >From: "Rad health" <healthrad@hotmail.com>
> >To: <info@eic.nu>; <radsafe@list.vanderbilt.edu>
> >Sent: Wednesday, January 16, 2002 8:18 PM
> >Subject: Re: Cohen's latest reward
> >
> >
> > > Kai,
> > >
> > > What emperical basis do you have to show that Cohen's inverse
> >relationship
> > > is not due to inter county variability?
> > >
> > > Don Smith
> > >
> > >
> > > >From: Kai Kaletsch <info@eic.nu>
> > > >To: Rad health <healthrad@hotmail.com>, radsafe@list.vanderbilt.edu
> > > >Subject: Re: Cohen's latest reward
> > > >Date: Wed, 16 Jan 2002 19:39:17 -0600
> > > >
> > > >Explaining a statistically strong association with "cross level bias
> >and
> > > >inter county variability" is like explaining the pollution in a lake
> >with
> > > >"all the dead fish that keep washing up on shore". Both the cross
level
> > > >bias
> > > >and the dead fish are symptoms of some more fundamental mechanism
that
> > > >needs
> > > >to be identified.
> > > >
> > > >Kai Kaletsch
> > > >
> > > >----- Original Message -----
> > > >From: "Rad health" <healthrad@HOTMAIL.COM>
> > > >To: <radsafe@list.vanderbilt.edu>
> > > >Sent: Wednesday, January 16, 2002 4:48 PM
> > > >Subject: Cohen's latest reward
> > > >
> > > >
> > > > > Dr. Cohen,
> > > >
> > > > >....one of the major factors,
> > > > > among others, most likely causing your paradoxical findings is
> > > >cross-level
> > > > > bias or inter county variability....
> > > >
> > > >
> > > >
> > >
> > >
> > > _________________________________________________________________
> > > Send and receive Hotmail on your mobile device: http://mobile.msn.com
> > >
> >
>
>
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