Interval estimation for treatment effects using propensity score matching.

Published

Journal Article

In causal studies without random assignment of treatment, causal effects can be estimated using matched treated and control samples, where matches are obtained using estimated propensity scores. Propensity score matching can reduce bias in treatment effect estimators in cases where the matched samples have overlapping covariate distributions. Despite its application in many applied problems, there is no universally employed approach to interval estimation when using propensity score matching. In this article, we present and evaluate approaches to interval estimation when using propensity score matching.

Full Text

Duke Authors

Cited Authors

  • Hill, J; Reiter, JP

Published Date

  • July 2006

Published In

Volume / Issue

  • 25 / 13

Start / End Page

  • 2230 - 2256

PubMed ID

  • 16220488

Pubmed Central ID

  • 16220488

Electronic International Standard Serial Number (EISSN)

  • 1097-0258

International Standard Serial Number (ISSN)

  • 0277-6715

Digital Object Identifier (DOI)

  • 10.1002/sim.2277

Language

  • eng