Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study.

Journal Article (Journal Article)

Estimation of treatment effects with causal interpretation from observational data is complicated because exposure to treatment may be confounded with subject characteristics. The propensity score, the probability of treatment exposure conditional on covariates, is the basis for two approaches to adjusting for confounding: methods based on stratification of observations by quantiles of estimated propensity scores and methods based on weighting observations by the inverse of estimated propensity scores. We review popular versions of these approaches and related methods offering improved precision, describe theoretical properties and highlight their implications for practice, and present extensive comparisons of performance that provide guidance for practical use.

Full Text

Duke Authors

Cited Authors

  • Lunceford, JK; Davidian, M

Published Date

  • October 15, 2004

Published In

Volume / Issue

  • 23 / 19

Start / End Page

  • 2937 - 2960

PubMed ID

  • 15351954

International Standard Serial Number (ISSN)

  • 0277-6715

Digital Object Identifier (DOI)

  • 10.1002/sim.1903

Language

  • eng

Conference Location

  • England