Propensity scores as a basis for equating groups: Basic principles and application in clinical treatment outcome research

Stephen West, Heining Cham, Felix Thoemmes, Babette Renneberg, Julian Schulze, Matthias Weiler

Research output: Contribution to journalArticle

53 Scopus citations

Abstract

A propensity score is the probability that a participant is assigned to the treatment group based on a set of baseline covariates. Propensity scores provide an excellent basis for equating treatment groups on a large set of covariates when randomization is not possible. This article provides a nontechnical introduction to propensity scores for clinical researchers. If all important covariates are measured, then methods that equate on propensity scores can achieve balance on a large set of covariates that mimics that achieved by a randomized experiment. We present an illustration of the steps in the construction and checking of propensity scores in a study of the effectiveness of a health coach versus treatment as usual on the well-being of seriously ill individuals. We then consider alternative methods of equating groups on propensity scores and estimating treatment effects including matching, stratification, weighting, and analysis of covariance. We illustrate a sensitivity analysis that can probe for the potential effects of omitted covariates on the estimate of the causal effect. Finally, we briefly consider several practical and theoretical issues in the use of propensity scores in applied settings. Propensity score methods have advantages over alternative approaches to equating groups particularly when the treatment and control groups do not fully overlap, and there are nonlinear relationships between covariates and the outcome.

Original languageEnglish (US)
Pages (from-to)906-919
Number of pages14
JournalJournal of consulting and clinical psychology
Volume82
Issue number5
DOIs
StatePublished - Jan 1 2014

Keywords

  • Group equating
  • Matching
  • Nonrandomized study
  • Propensity scores

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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