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Interval estimation for treatment effects using propensity score matching
Author(s) -
Hill Jennifer,
Reiter Jerome P.
Publication year - 2005
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2277
Subject(s) - propensity score matching , covariate , matching (statistics) , statistics , estimator , confidence interval , average treatment effect , interval (graph theory) , interval estimation , random assignment , causal inference , mathematics , econometrics , combinatorics
Abstract 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. Copyright © 2005 John Wiley & Sons, Ltd.