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January 1, 1984Biometrika690 citations

Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates

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MGMitchell H. GailSWSam WieandSPSteven Piantadosi

Key Points

  • The aim is to identify biases in treatment effect estimates caused by omitted covariates in nonlinear regression models.
  • Analyzed treatment effects using nonlinear regression models.
  • Considered the impact of omitted covariates on effect estimates.
  • Performed statistical comparisons to evaluate bias.
  • Found significant bias in treatment effect estimates due to omitted covariates.
  • Demonstrated that bias varied depending on the structure of nonlinear regressions.
  • Highlighted the necessity for careful covariate selection in experimental designs.

Abstract

Journal Article Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates Get access M. H. GAIL, M. H. GAIL Biometry Branch of the Division of Cancer Prevention and Control, National Cancer InstituteBethesda, Maryland, U.S.A. Search for other works by this author on: Oxford Academic Google Scholar S. WIEAND, S. WIEAND Department of Mathematics and Statistics, University of PittsburghPittsburgh, Pennsylvania, U.S.A. Search for other works by this author on: Oxford Academic Google Scholar S. PIANTADOSI S. PIANTADOSI Biometry Branch of the Division of Cancer Prevention and Control, National Cancer InstituteBethesda, Maryland, U.S.A. Search for other works by this author on: Oxford Academic Google Scholar Biometrika, Volume 71, Issue 3, December 1984, Pages 431–444, https://doi.org/10.1093/biomet/71.3.431 Published: 01 December 1984 Article history Received: 01 December 1983 Revision received: 01 April 1984 Published: 01 December 1984

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Cite This Study

Gail et al. (1984) studied this question.

synapsesocial.com/papers/6a08848d7de338f10b10bf9bhttps://doi.org/10.1093/biomet/71.3.431
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