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Abstract

Many studies use the same variable, for example blood pressure in studies of antihypertensive treatments, to identify subjects to be included in the study and to evaluate the effects of a treatment. As a consequence, if not properly accounted for, the effect of regression toward the mean can confound the evaluation of treatment effects if the study has no randomized control group. In this paper we review the methods that have been proposed for adjusting for the effect of regression toward the mean when the variable of interest is assumed to be normally distributed. Maximum likelihood estimation and moment-based estimation are considered, including more recent methods which can be applied when repeated measurements on each subject are available.

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Adjusting for regression toward the mean when variables are normally distributed

Abstract

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