期刊
BIOMETRIKA
卷 96, 期 1, 页码 37-50出版社
OXFORD UNIV PRESS
DOI: 10.1093/biomet/asn069
关键词
Missing not at random; Multiple imputation; Nonignorable missingness
资金
- U. S. National Institute on Drug Abuse
When an assumption of missing at random is untenable, it becomes necessary to model missing-data indicators, which carry information about the parameters of the complete-data population. Within a given application, however, researchers may believe that some aspects of missingness are ignorable but others are not. We argue that there are two different ways to formalize the notion that only part of the missingness is ignorable. These approaches correspond to assumptions that we call partially missing at random and latently missing at random. We explain these concepts and apply them in a latent-class analysis of survey questions with item nonresponse.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据