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st: RE: RE: RE: unpaired regression


From   "Wallace, John" <John_Wallace@affymetrix.com>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: RE: unpaired regression
Date   Wed, 12 May 2004 08:57:05 -0700

First of all, thanks for the discussion, Buzz, Nick and David.  Its allowing
me to look at the problem in different ways.  David's suggestion below is an
interesting take - I do expect a systematic covariance between both assay
measures.  Since batch isn't a continuous variable I hadn't thought of
putting it on an axis.
Assay1 is a high-throughput, simplified model for predicting the response of
the batch to assay2.  The replicates are randomized from the batch, so
there's little systematic structure to the order of the replicates (which is
why I'm hesitant to pair them up).

-----Original Message-----
From: David Airey [mailto:david.airey@vanderbilt.edu] 
Sent: Wednesday, May 12, 2004 8:34 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: RE: unpaired regression

> Can anyone comment on whether Scott's suggestion would be appropriate 
> for
> the problem I'm working on?  The difference in R^2 between the samples
> indicates that it might be problematic.


I'm not clear what the questions/hypotheses are. You have a grouping, 
and two measures. Are you thinking of these two measures as response or 
predictor? If response, then what about a MANOVA framework, where you 
have batch as X1, and replicated assays as Y1 and Y2?

-Dave

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