Recommendation to resolve Cohen's ecologic study questions

["Field, R. William" <bill-field@UIOWA.EDU>]

Dr. Cohen,


Here is my specific recommendation. 

If you are really interested in using your ecologic data and getting at

the potential sources of your bias, you need to identify what inter

county adjustments need to be made by using more innovative

methods.  Possibly those suggested in: Guthrie, KA and Sheppard, L,

Overcoming biases and misconceptions in ecological studies, J.R. Statist.

Soc., volume 164, pp 141-154, 2001.


In your past stratifications, you have confused individual level

confounding with group level confounding.  You can not hope to

correct for bias in your ecologic model by using stratification based on

individual level model confounders when your model has non-linear and

non-additive effects.  Therefore, if you hope to explain your

findings, you need to use aggregate level confounder models possibly

using the aggregate data approach as specified by Guthrie and

Sheppard.  However, this will require some data collection on your

part.  


I would be happy to fax you the paper if you are interested.  I wish

you good luck.


Regards, Bill Field



Regards, Bill Field


R. William Field, M.S,

Ph.D.

College of Public Health

Research Scientist - Department of Epidemiology

Adjunct Professor - Department of Occupational and Environmental

Health

Graduate Faculty - College of Public Health 

N222 Oakdale Hall

University of Iowa

Iowa City, Iowa  52242


319-335-4413 (phone)

319-335-4748 (fax)

mailto:bill-field@uiowa.edu



At 12:48 PM 01/22/2002 -0500, BERNARD L COHEN wrote:

> 2) They continue to say that cross-level bias and inter county variability
> caused your findings.  Do you really have the data to show this is not the
> case?

        --I need a specific example -- see above. If a specific example is
offered, it is up to me to supply the data required.

> My most important question about the Field and Smith paper:  Are adjustments
> made using aggregate data (smoking, education, etc.)usually used to adjust
> for confounding at the individual level - sufficient for use in adjusting at
> the county level?

        --I do not "adjust" my data for anything. I treat confounding by
my method of stratification which is very much superior.

>  From reading their papers they say you may never find
> your answer because your data are lacking.  Can you really say you have
> tested all the possibilities if you do not have the data you need to adjust
> for aggregate confounding?

        --Providing the data is my problem. What I need is a
specific suggestion for which data are needed.

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