Bayesian Approaches for Missing Not at Random Outcome Data: The Role of Identifying Restrictions.
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ABSTRACT:
SUBMITTER: Linero AR
PROVIDER: S-EPMC6936760 | biostudies-literature | 2018 May
REPOSITORIES: biostudies-literature
Publications
Bayesian Approaches for Missing Not at Random Outcome Data: The Role of Identifying Restrictions.
Linero Antonio R AR Daniels Michael J MJ
Statistical science : a review journal of the Institute of Mathematical Statistics 20180503 2
Missing data is almost always present in real datasets, and introduces several statistical issues. One fundamental issue is that, in the absence of strong uncheckable assumptions, effects of interest are typically not nonparametrically identified. In this article, we review the generic approach of the use of identifying restrictions from a likelihood-based perspective, and provide points of contact for several recently proposed methods. An emphasis of this review is on restrictions for nonmonoto ...[more]
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