Cited by 3,082Advanced Causal Inference TechniquesStatistical Methods in Clinical TrialsMeta-analysis and systematic reviews

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Reducing Bias in Observational Studies Using Subclassification on the Propensity Score

Rosenbaum, Paul R., Rubin, Donald B.·1984·Journal of the American Statistical Association

DOI 10.1080/01621459.1984.10478078

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Abstract

The propensity score is the conditional probability of assignment to a particular treatment given a vector of observed covariates. Previous theoretical arguments have shown that subclassification on the propensity score will balance all observed covariates. Subclassification on an estimated propensity score is illustrated, using observational data on treatments for coronary artery disease. Five subclasses defined by the estimated propensity score are constructed that balance 74 covariates, and thereby provide estimates of treatment effects using direct adjustment. These subclasses are applied within sub-populations, and model-based adjustments are then used to provide estimates of treatment effects within these sub-populations. Two appendixes address theoretical issues related to the application: the effectiveness of subclassification on the propensity score in removing bias, and balancing properties of propensity scores with incomplete data.

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Nonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1958) · Journal of the American Statistical Association · doi:10.1080/01621459.1958.10501452 · Cited by 39,158
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Self-citation
Exploratory Data Analysis
David, F. N., & Tukey, J. W. (1977) · Biometrics · doi:10.2307/2529486 · Cited by 12,707
BMD : biomedical computer programs
Dixon, W. J. (1965) · University of California Press eBooks · Cited by 2,673
Bayesian inference for causal effects: The role of randomization
Rubin, D. B. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344064 · Cited by 2,503
Self-citation
Conditional Independence in Statistical Theory
Dawid, A. P. (1979) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1979.tb01052.x · Cited by 1,507
Data Analysis and Regression.
Osborn, J. F., Mosteller, F. C., & Tukey, J. W. (1978) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344493 · Cited by 1,465
Discrete Multivariate Analysis.
Gokhale, D. V., Bishop, Y. M. M., Fienberg, S. E., & Holland, P. W. (1976) · Biometrics · doi:10.2307/2529528 · Cited by 1,287
Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome
Rosenbaum, P., & Rubin, D. B. (1983) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1983.tb01242.x · Cited by 1,128
Self-citation
The NEW ENGLAND JOURNAL of MEDICINE
Gelijns, A. C., Rosenberg, N., & Moskowitz, A. J. (2009) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789814273596_0013 · Cited by 1,012

Show all 15 references

Research works printed but not linked: 3

Cochran W. G., 1973, Sankya, 35, 417
Cox D. R., 1970, The Analysis of Binary Data
Rubin D. B., 1970, “The Use of Matched Sampling and Regression Adjustment in Observational Studies

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Authors: Rosenbaum, P. R., & Rubin, D. B.
Affiliations: Educational Testing Service (US)
University of Chicago (US)
ORCID: Rosenbaum, Paul R.
Rubin, Donald B.
Venue: Journal of the American Statistical Association
Publisher: Informa UK Limited
Published: 1984-09
Volume: 79
Issue: 387
Pages: 516-524
ISSN: 0162-1459 (ISSN-L)
1537-274X
DOI: 10.1080/01621459.1984.10478078
OpenAlex: W4239728164
Cited by: 3,082
References: 15
Citations by year: 2026: 100 · 2025: 128 · 2024: 140 · 2023: 136 · 2022: 142 · 2021: 175 · 2020: 154 · 2019: 147 · 2018: 164 · 2017: 147 · 2016: 169 · 2015: 133 · 2014: 178 · 2013: 143 · 2012: 140
FWCI: 5.43
Type: journal article
Language: en
Open access: closed
Locations: Journal of the American Statistical Association (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords: propensity score, subclassification, observational studies, bias mitigation, covariate balance, treatment effect estimation, coronary artery disease, missing data

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Reducing Bias in Observational Studies Using Subclassification on the Propensity Score

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