PATTERN GRAPHS: A GRAPHICAL APPROACH TO NONMONOTONE MISSING DATA

• 成果类型: Article
• 署名作者: Chen, Yen-Chi
• 署名单位: University of Washington; University of Washington Seattle
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/21-AOS2094
• 发表日期: 2022
• 页码: 129-146
• 关键词: nonparametric analysis; nonresponse models

摘要

We introduce the concept of pattern graphs-directed acyclic graphs representing how response patterns are associated. A pattern graph represents an identifying restriction that is nonparametrically identified/saturated and is often a missing not at random restriction. We introduce a selection model and a pattern mixture model formulations using the pattern graphs and show that they are equivalent. A pattern graph leads to an inverse probability weighting estimator as well as an imputation-based estimator. We also study the semiparametric efficiency theory and derive a multiply-robust estimator using pattern graphs.