Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data.

Published

Journal Article

Considerable recent interest has focused on doubly robust estimators for a population mean response in the presence of incomplete data, which involve models for both the propensity score and the regression of outcome on covariates. The usual doubly robust estimator may yield severely biased inferences if neither of these models is correctly specified and can exhibit nonnegligible bias if the estimated propensity score is close to zero for some observations. We propose alternative doubly robust estimators that achieve comparable or improved performance relative to existing methods, even with some estimated propensity scores close to zero.

Full Text

Duke Authors

Cited Authors

  • Cao, W; Tsiatis, AA; Davidian, M

Published Date

  • September 2009

Published In

Volume / Issue

  • 96 / 3

Start / End Page

  • 723 - 734

PubMed ID

  • 20161511

Pubmed Central ID

  • 20161511

International Standard Serial Number (ISSN)

  • 0006-3444

Digital Object Identifier (DOI)

  • 10.1093/biomet/asp033

Language

  • eng

Conference Location

  • England