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st: baseline adjustment in mixed models


From   "Visintainer PhD, Paul" <Paul.Visintainer@baystatehealth.org>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: baseline adjustment in mixed models
Date   Fri, 13 Nov 2009 14:34:54 -0500

Hello everyone,

I have a question about baseline adjustment . . .

Do random intercept models (RI) or random coefficient models (RC) account for group differences in the baseline value of the outcome?  I'm not asking the general question of whether or not we should control for baseline values (there is a lot of literature on this), but rather, with RI or RC models is it even necessary? 

Suppose in a clinical trial, where outcome is measured on multiple occasions over time, randomization did not achieve balance between treatment and control groups on the initial value (Y0), is it necessary to control for the baseline value of the outcome in a RI or RC model?  Is it redundant?  Does it improve precision or efficiency?  (Let's assume the outcome is continuous, rather than categorical).

I'd appreciate any opinions.

Thanks,

Paul
___________________________________
Paul F. Visintainer, PhD
Springfield, MA 01199

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