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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.


  1. Anonymous (2020), 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.