American Journal of Ophthalmology
Volume 149, Issue 1 , Pages 7-9 , January 2010

Propensity Score Methods

  • Donald B. Rubin

      Affiliations

    • Corresponding Author InformationInquiries to Donald B. Rubin, Department of Statistics, Harvard University, Science Center Room 716, 1 Oxford Street, Cambridge, MA 02138

,Accepted 20 August 2009.

References 

  1. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55
  2. Milton RC, Sperduto RD, Clemons TE, Ferris FL Age-Related Eye Disease Study Research Group. Centrum use and progression of age-related cataract in the Age-Related Eye Disease Study: a propensity score approach. Ophthalmology. 2006;113:1264–1270
  3. Rubin DB. The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials. Stat Med. 2007;26:20–30
  4. Rubin DB. For objective causal inference, design trumps analysis. Ann Appl Stat. 2008;2:808–840
  5. Cochran WG. The effectiveness of adjustment by subclassification in removing bias in observational studies. Biometrics. 1968;24:295–313
  6. Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score. J Am Stat Assoc. 1984;79:516–524
  7. General Accounting Office. Breast conservation versus mastectomy: patient survival in day-to-day medical practice and randomized studies. Washington D.C: U.S. General Accounting Office; 1994;Report GAO-PEMD-95-9
  8. Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med. 1997;127:757–763
  9. Rosenbaum PR, Rubin DB. Assessing sensitivity to an unobserved binary covariate in an observational study with binary outcome. J R Stat Soc Series B Stat Methodol. 1983;45:212–218

PII: S0002-9394(09)00625-4

doi: 10.1016/j.ajo.2009.08.024

American Journal of Ophthalmology
Volume 149, Issue 1 , Pages 7-9 , January 2010

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