The Central Role of the Propensity Score in Observational Studies for Causal Effects.

Abstract

The results of observational studies are often disputed because of nonrandom treatment assignment. For example, patients at greater risk may be overrepresented in some treatment group. This paper discusses the central role of propensity scores and balancing scores in the analysis of observational studies. The propensity score is the (estimated) conditional probability of assignment to a particular treatment given a vector of observed covariates. Both large and small sample theory show that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates. Applications include: matched sampling on the univariate propensity score which is equal percent bias reducing under more general conditions than required for discriminant matching, multivariate adjustment by subclassification on balancing scores where the same subclasses are used to estimate treatment effects for all outcome variables and in all subpopulations, and visual representation of multivariate adjustment by a two-dimensional plot. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA114514

Entities

People

  • Donald B. Rubin
  • Paul R. Rosenbaum

Organizations

  • University of Wisconsin–Madison

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DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Contracts
  • Covariance
  • Data Mining
  • Data Science
  • Environmental Protection
  • Experimental Design
  • Information Science
  • Mathematics
  • Monotone Functions
  • Probability
  • Sampling
  • Statistical Algorithms
  • Statistics
  • United States
  • Wisconsin

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.