On protected estimation of an odds ratio model with missing binary exposure and confounders

• 成果类型: Article
• 署名作者: Tchetgen, E. J. Tchetgen; Rotnitzky, A.
• 署名单位: Harvard University; Harvard T.H. Chan School of Public Health; Universidad Torcuato Di Tella
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asr027
• 发表日期: 2011
• 页码: 749754
• 关键词: doubly robust estimation; logistic-regression; covariate data; inference

摘要

We describe an estimator of the parameter indexing a model for the conditional odds ratio between a binary exposure and a binary outcome given a high-dimensional vector of confounders, when the exposure and a subset of the confounders are missing, not necessarily simultaneously, in a subsample. We argue that a recently proposed estimator restricted to complete-cases confers more protection to model misspecification than existing ones in the sense that the set of data laws under which it is consistent strictly contains each set of data laws under which each of the previous estimators are consistent.