Adjustment for confounding

[FIELDRW@aol.com]

In a message dated 3/9/00 11:09:39 AM Central Standard Time, blc+@pitt.edu 
writes:

<<  --My study avoids the problem of non-linearity by using
 "Stratification". For example, if one worries about population density as
 a confounding factor, I do a complete analysis utilizing only data from
 counties that have nearly the same population density. I do this for many
 different population densities, and I always get the same result, without
 assuming that anything is linear with population density.
    The reason I am able to do this is because I have 1600 counties in
 my data files, whereas 160 counties is enough for doing a complete
 analysis with little statistical uncertainty. 
    I also have a treatment of multiple confounding factors, but that
 is too complex to summarize here.  >>


Dr. Cohen, You are not able to adjust for multiple differences within or 
between counties at the same time such as differences is smoking rates, age, 
education etc, etc.  Adjustment using more summary averaged data is 
inadequate to control for confounding.

Bill Field
bill-field@uiowa.edu  
************************************************************************
The RADSAFE Frequently Asked Questions list, archives and subscription
information can be accessed at http://www.ehs.uiuc.edu/~rad/radsafe.html