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Propensity score

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In statistics, a propensity score is a "conditional probability of exposure to a treatment given observed covariates."[1][2]

The propensity score was introduced by Rosenbaum in 1983.[3][4] The propensity score is the "conditional probability of receiving one of the treatments under comparison ... given the observed covariates."[5] The propensity score can only correct for confounding by independent variables that have been measured.

References[edit]

  1. Anonymous (2023), Propensity score (English). Medical Subject Headings. U.S. National Library of Medicine.
  2. Griswold ME, Localio AR, Mulrow C (2010). "Propensity score adjustment with multilevel data: setting your sites on decreasing selection bias.". Ann Intern Med 152 (6): 393-5. DOI:10.1059/0003-4819-152-6-201003160-00010. PMID 20231571. Research Blogging.
  3. Rosenbaum PR, Rubin DB (1983). "The central role of the propensity score in observational studies for causal effects". Biometrika 70 (1): 41. DOI:10.1093/biomet/70.1.41. Research Blogging.
  4. Hill J (April 2008). "Discussion of research using propensity-score matching: Comments on 'A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003' by Peter Austin, Statistics in Medicine". Stat Med 27 (12): 2055–2061. DOI:10.1002/sim.3245. PMID 18446836. Research Blogging.
  5. Schmoor C, Caputo A, Schumacher M (2008). "Evidence from nonrandomized studies: a case study on the estimation of causal effects.". Am J Epidemiol 167 (9): 1120-9. DOI:10.1093/aje/kwn010. PMID 18334500. Research Blogging.

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