Maximum Likelihood Estimation of Treatment Effects for Samples Subject to Regression to the Mean

Stephen Senn, Richard Brown

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)

Abstract

A general maximum likelihood approach for estimating the effects of treatments applied to samples subject to regression to the mean is outlined. Models may be specified in terms of three factors: whether the treatment effect is multiplicative or additive, whether the treatment group is above or below some truncation point and the type of sample involved. The way in which solutions may be obtained for all 16 models so defined is described.

Original languageEnglish
Pages (from-to)3389-3406
Number of pages18
JournalCommunications in Statistics - Theory and Methods
Volume18
Issue number9
DOIs
Publication statusPublished - Jan 1989
Externally publishedYes

Keywords

  • bivariate normal
  • censored
  • regression to the mean
  • truncated

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