Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score

1985/02/01 by Paul R. Rosenbaum, Donald B. Rubin · 4,335 citations
Mathematics · #Advanced Causal Inference Techniques #Causal inference #Computer science #Covariate #Econometrics #Matching (statistics) #Mathematics #Multivariate analysis #Multivariate statistics #Observational study #Propensity score matching #Random assignment #Sampling (signal processing) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics #Treatment and control groups

paper · doi:10.1080/00031305.1985.10479383

published in The American Statistician 39(1), 33-38 (Taylor & Francis)

openalex publication_date 1985/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Matched sampling is a method for selecting units from a large reservoir of potential controls to produce a control group of modest size that is similar to a treated group with respect to the distribution of observed covariates. We illustrate the use of multivariate matching methods in an observational study of the effects of prenatal exposure to barbiturates on subsequent psychological development. A key idea is the use of the propensity score as a distinct matching variable.

Citations

• The central role of the propensity score in observational studies for causal effects

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