Effect of regression to the mean in the presence of within‐subject variability

William D. Johnson, Varghese T. George

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Regression to the mean arises often in statistical applications where the units chosen for study relate to some observed characteristic in the extreme of its distribution. Gardner and Heady attribute the effect of regression to the mean to measurement errors. They assume the modelYi = U + ei, where U is a fixed within‐subject component and ei is the random measurement error. They suggest several replicate measurements to reduce the regression effect under the assumption that the measurement errors ei are independent within subjects. While measurement errors play an important role in regression to the mean, one should not overlook within‐subject variation. In this paper, we consider a model to estimate the regression effect in the presence of correlated within‐subject effects as well as independent measurement errors.

Original languageEnglish (US)
Pages (from-to)1295-1302
Number of pages8
JournalStatistics in Medicine
Volume10
Issue number8
DOIs
StatePublished - Aug 1991
Externally publishedYes

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

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