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Re: Cohen's latest reward
From: Kai Kaletsch <info@eic.nu>>Don,
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.
--------------
Kai, No, what you are talking about above is called the ecologic fallacy.
You are confusing the ecologic fallacy with cross-level bias and intra/inter
county bias.
Don Smith
---------------
> > 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....
> > > > >
> > > > >
> > > > >
> > > >
> > > >
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