Effect of regression to the mean in multivariate distributions

Varghese T. George, William D. Johnson

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Estimating treatment effects in the presence of regression to the mean is a problem arising in truncated distributions that is being recognized with increasing interest in recent literature. As noted in a previous communication by the authors (1991), any extraneous source of variability such as within-subject variability and measurement errors can contribute to the magnitude of regression toward the mean. The main focus of this paper is consideration of a model for estimating treatment effects when truncation and regression to the mean occur on more than one random variable. This situation occurs often in investigations where subjects are selected for study because measurements on two characteristics of interest both exceed specified values.

Original languageEnglish (US)
Pages (from-to)333-350
Number of pages18
JournalCommunications in Statistics - Theory and Methods
Issue number2
StatePublished - Jan 1 1992
Externally publishedYes


  • bivariate normal distribution
  • measurement error
  • regression to the mean
  • repeated measurements
  • replicate measurements
  • truncation
  • within-subject effect

ASJC Scopus subject areas

  • Statistics and Probability


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