Balanced Subclassification in Observational Studies Using the Propensity Score: A Case Study.

Abstract

The propensity score is the conditional probability of assignment to a particular treatment given a vector of observed covariates. Previous theeoretical arguments have shown that subclassification on the scalar propensity score will balance all observed covariates. The procedure is illustrated in a large observational study of treatments for coronary artery disease. Five subclasses are constructed that balance 74 covariates. Balanced subclassification is combined with model-based adjustments to provide estimates of treatment effects within subpopulations. Two appendices address theoretical issues: propensity scores from incomplete data, and the effectiveness of subclassification on the propensity score.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1983
Accession Number
ADA127760

Entities

People

  • Donald B. Rubin
  • Paul R. Rosenbaum

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Case Studies
  • Data Analysis
  • Data Science
  • Diseases And Disorders
  • Education
  • Information Science
  • Mathematics
  • Myocardial Ischemia
  • Neoplasms
  • Probability
  • Scalar Functions
  • Statistics
  • Surgery
  • Theorems
  • Therapy
  • United States
  • Universities

Fields of Study

  • Mathematics

Readers

  • Psychometric Testing or Psychological Assessment.
  • Statistical inference.
  • Systems Analysis and Design