Tchetgen Tchetgen E J, Rotnitzky A
Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, U.S.A. ,
Biometrika. 2011 Sep;98(3):749-754. doi: 10.1093/biomet/asr027.
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.
我们描述了一种参数估计量，该参数为给定高维混杂因素向量时二元暴露与二元结局之间条件优势比的模型建立索引。当暴露和一部分混杂因素在子样本中缺失（不一定同时缺失）时，我们讨论了一种最近提出的仅限于完整病例的估计量，与现有估计量相比，它在模型误设方面具有更强的保护作用，因为它一致的数据律集合严格包含了之前每个估计量一致的数据律集合。
