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Cited by 2,228Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyStatistical Methods in Clinical Trials

The DOI matches its Crossref record; 49 of the 51 references it cites were found in a registry or an index.

Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation

Rubin, Donald B.·2001·Health Services and Outcomes Research Methodology
DOI 10.1023/a:1020363010465
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Crossref · 10.1023/a:1020363010465

Cites

49 of 49 references verified0 citation errors · 0 not checkable

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Citations

Cites

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2 of the 51 references couldn’t be matched to a known paper.

Research works printed but not linked: 10

  1. AHCPR, “National medical expenditure survey, calendar year 1987,” Center for General Health Services Research, Agency for Health Care Policy and Research, Public Health Service: Rockville,MD, 1992.
  2. D. J. Benjamin, “Does 401(k) eligibility increase net national savings?: reducing bias in the eligibility effect estimate,” A. B. Honors Thesis in Economics, Harvard University, Cambridge, MA, 1999.
  3. GAO (U.S. General Accounting Office), “Breast conservation versus mastectomy: patient survival in day-to-day medical practice and randomized studies,” Report #GAO-PEMD-95-9, U.S. General Accounting Office: Washington, D.C., 1995.
  4. G. W. Harrison, ‘Expert Report, April 27, 1998: “Health care expenditures attributable to smoking in Oklahoma,”’ The State of Oklahoma, ex rel., et al., Plaintiffs, vs. Reynolds Tobacco Co., et al., Defendants, Case No. CJ-96-1499-L, District Court of Cleveland County, Oklahoma, 1998.
  5. J. Hill, D. B. Rubin and N. Thomas, “The design of the New York school choice scholarship program evaluation,” in Research Designs: Inspired by the Work of Donald Campbell, (L. Bickman, ed.), Sage Publications, Thousand Oaks, CA, 155-180, 1999.
  6. L. Roseman, “Reducing bias in the estimate of the difference in survival in observational studies using subclassification on the propensity score,” Ph.D. Thesis, Department of Statistics, Harvard University, Cambridge, MA, 1998.
  7. P. R. Rosenbaum and D. B. Rubin, “Constructing a control group using multivariate matched sampling incorporating the propensity score,” The American Statistician, 39, pp. 33-38, 1985. · DOI
  8. D. B. Rubin, “The use of matched sampling and regression adjustment in observational studies,” Ph.D. Thesis, Department of Statistics, Harvard University: Cambridge, MA, 1970.
  9. D. B. Rubin, “William, G. Cochran's contributions to the design, analysis, and evaluation of observational studies,” in W. G. Cochran's Impact on Statistics ( Rao and Sedransk, eds.), John Wiley, New York, pp. 37-69, 1984.
  10. D. B. Rubin, “Statistical assumptions in the estimation of the causal effects of smoking due to the conduct of the tobacco industry,” in Social Science Methodology in the New Millennium. Proceedings of the Fifth International Conference on Logic and Methodology (J. Blasius, J. Hox, E. de Leeuw and P. Schmidt, eds.), October 6, 2000, Cologne, Germany, 1-22, 2000b.

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Metadata

Authors
Rubin, D. B.
Affiliations
Harvard University (US)
Corresponding author
Rubin, Donald B.
ORCID
Rubin, Donald B.
Venue
Health Services and Outcomes Research Methodology
Publisher
Springer Science and Business Media LLC
Published
2001-12
Volume
2
Issue
3-4
Pages
169-188
ISSN
  • 1387-3741 (ISSN-L)
  • 1572-9400
DOI
10.1023/a:1020363010465
OpenAlex
W2597503617
Cited by
2,228
References
51
Citations by year
2026: 174 · 2025: 193 · 2024: 196 · 2023: 175 · 2022: 172 · 2021: 166 · 2020: 173 · 2019: 163 · 2018: 123 · 2017: 100 · 2016: 93 · 2015: 75 · 2014: 77 · 2013: 72 · 2012: 44
FWCI
4.04
Type
journal article
Language
en
Open access
closed
Licence
Locations
Health Services and Outcomes Research Methodology (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords
propensity score, observational study design, covariate balance, matching, subclassification, weighting, diagnostic tables, treatment effect estimation, tobacco litigation, National Medical Expenditure Survey, causal inference

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