articleStatistics in MedicineMay 17, 2006Closed access

A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study

University of Toronto · Institute for Clinical Evaluative Sciences

PubMed
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Abstract

The propensity score--the probability of exposure to a specific treatment conditional on observed variables--is increasingly being used in observational studies. Creating strata in which subjects are matched on the propensity score allows one to balance measured variables between treated and untreated subjects. There is an ongoing controversy in the literature as to which variables to include in the propensity score model. Some advocate including those variables that predict treatment assignment, while others suggest including all variables potentially related to the outcome, and still others advocate including only variables that are associated with both treatment and outcome. We provide a case study of the…

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Topics & keywords

Keywords
  • Propensity score matching
  • Confounding
  • Observational study
  • Outcome (game theory)
  • Statistics
  • Matching (statistics)
  • Medicine
  • Average treatment effect
UN Sustainable Development Goals
  • Good health and well-being
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