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Date:         Wed, 17 Dec 2008 10:46:05 -0600
Reply-To:     Mary <mlhoward@avalon.net>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Mary <mlhoward@AVALON.NET>
Subject:      Re: Regression: do you always need main effects with interactions?
Comments: To: Peter Flom <peterflomconsulting@mindspring.com>
Content-Type: text/plain; charset="utf-8"

Yes, this is a very interesting area of research right now, especially in outcomes analysis of health care treatments; we can look at outcome result by the characteristics of the patient, such as including variables for genetic haplotypes in models predicting whether the patient improves given a particular treatment regimen. This will guide doctors and patients in deciding whether a course of treatment is likely to be a success given a particular patient's demographic and genetic characteristics, and hopefully can cut down on the time and expense of giving uneffective treatments to people unlikely to do well under them.

I can see that it would apply to other areas of research as well, such as in education where children of certain temperament and genetic characteristics might learn better in certain environments (such as web learning versus classroom learning) than others.

-Mary ----- Original Message ----- From: Peter Flom To: SAS-L@LISTSERV.UGA.EDU Sent: Wednesday, December 17, 2008 9:33 AM Subject: Re: Regression: do you always need main effects with interactions?

>The age of using the general term "patient" is over, or should be. Any >relationship you find with those 1000 variables may need to be refined. To >illustrate, no longer should doctors say "patients given aspirin experience >fewer acute coronary events." Patients differ in too many meaningful >variables, especially genetic, which we are revealing every day. >

Indeed.

This is a pet peeve of mine, that we often see statements that ignore human variation.

Peter

Peter L. Flom, PhD Statistical Consultant www DOT peterflom DOT com


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