Matching to Remove Bias in Observational Studies.

Abstract

Several matching methods that match all of one sample from another larger sample on a continuous matching variable are compared with respect to their ability to remove bias under a simple linear model. One method is a simple mean-matching method and three are nearest available pair-matching methods. The methods' abilities to remove bias are also compared with the theoretical maximum given fixed distributions and fixed sample sizes. A summary of advice to an investigator is included. (Author)

Document Details

Document Type
Technical Report
Publication Date
Dec 14, 1970
Accession Number
AD0716441

Entities

People

  • Donald B. Rubin

Organizations

  • Harvard University

Tags

Fields of Study

  • Mathematics

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Calculus or Mathematical Analysis
  • Computational Modeling and Simulation