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Date:         Tue, 10 Jul 2007 05:07:09 -0700
Reply-To:     Paige Miller <paige.miller@KODAK.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Paige Miller <paige.miller@KODAK.COM>
Organization: http://groups.google.com
Subject:      Re: Can I do this multiplr regression?
Comments: To: sas-l@uga.edu
In-Reply-To:  <BAY103-F16165A33CAB1BFEDBF6FACB0050@phx.gbl>
Content-Type: text/plain; charset="us-ascii"

On Jul 10, 2:28 am, davidlcass...@MSN.COM (David L Cassell) wrote: > x...@LSU.EDU wrote: > > >A colleague asked me if he can do this multiple regression. He first > >calculated differences from X1 and X2 and used it as the dependent variable > >(Y). Then he wanted to run regression Y = X0 X1 X3 X4 where Y is the > >difference between X1 and X2, and he wanted to put X1 as one predictor. X0, > >X3, X4 are independent from Y. > > >Can this multiple regression be done? Which assumption is violated? > > This, in itself, does not violate any regression assumptions. Of course: > > [1] regression assumptions may be violated that have nothing to do with > using Y=X1-X2. > > and > > [2] there may be serious logical violations in doing this. > > #2 depends on the data, the meaning of the variables, the underlying > theory involved, the scope of the data, etc. It may be entirely feasible > to perform the regression, even though scientifically it could be a hideous > nightmare. I think this is a subject-matter problem more than a > statistical one.

I would add that since Y is a function of X1 and other variables, then putting X1 in the right hand side as a predictor is very problematic.

Specifically, Y may be highly correlated with X1. Now that in itself isn't a problem. The problem is that if the large regression doesn't improve the fit over the regression involving Y and only X1 and an intercept, then the large regression is useless. It simply is explaining the a priori correlation between Y and X1.

-- Paige Miller paige\dot\miller \at\ kodak\dot\com


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