ArticleStatistical science : a review journal of the Institute of Mathematical Statistics2018
Bayesian Approaches for Missing Not at Random Outcome Data: The Role of Identifying Restrictions.
Article in Statistical science : a review journal of the Institute of Mathematical Statistics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Repurposing semaglutide as an adjunctive treatment for cocaine use disorder: protocol for a randomised controlled trial.BMJ open · 2026Article
- Associations of lifetime cumulative estrogen exposure with lifecourse social exposures, cognitive decline, and dementia risk among postmenopausal White, Black, and Latina women.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026Article
- Longitudinal Examination of Loneliness and Smoking in Adolescents and Young Adults: A Multiple Dataset Study.International journal of mental health and addiction · 2026Article
- A Fully-Integrated Bayesian Approach for the Imputation and Analysis of Derived Outcome Variables With Missingness.Statistics in medicine · 2026Article
- Short-chain per- and polyfluoroalkyl substances associate with elevated alanine aminotransferase: Cross-sectional analysis results from the STRIVE cohort.Environmental research · 2025Article
- Pattern Mixture Sensitivity Analyses via Multiple Imputations for Non-Ignorable Dropout in Joint Modeling of Cognition and Risk of Dementia.Statistics in medicine · 2025Article
- Accounting for bias due to outcome data missing not at random: comparison and illustration of two approaches to probabilistic bias analysis: a simulation study.BMC medical research methodology · 2024Article
- Sensitivity analysis for studies transporting prediction models.Biometrics · 2024Article
- The Impact of Sparse Datasets When Harmonizing Data from Studies with Different Measures of the Same Construct.Prevention science : the official journal of the Society for Prevention Research · 2024Article
- Bayesian regression analysis of skewed tensor responses.Biometrics · 2023Article
- Methods for handling missing binary data in substance use disorder trials.Drug and alcohol dependence · 2023Review
- Causal mediation and sensitivity analysis for mixed-scale data.Statistical methods in medical research · 2023Article
- Hierarchical Bayesian non-response models for error rates in forensic black-box studies.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Article
- Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Controls in Clinical Trials.Journal of the American Statistical Association · 2023Article
- Sensitivity analyses for data missing at random versus missing not at random using latent growth modelling: a practical guide for randomised controlled trials.BMC medical research methodology · 2022Article
- Global sensitivity analysis of randomized trials with nonmonotone missing binary outcomes: Application to studies of substance use disorders.Biometrics · 2022Article
- Errors in the implementation, analysis, and reporting of randomization within obesity and nutrition research: a guide to their avoidance.International journal of obesity (2005) · 2021Review
- Adjusting for selection bias due to missing data in electronic health records-based research.Statistical methods in medical research · 2021Article
- Bayesian semi-parametric G-computation for causal inference in a cohort study with MNAR dropout and death.Journal of the Royal Statistical Society. Series C, Applied statistics · 2021Article
- Nonstandard conditionally specified models for nonignorable missing data.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
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 nonmonotone missingness, a subject that has been treated sparingly in the literature. We also present a general, fully-Bayesian, approach which is widely applicable and capable of handling a variety of identifying restrictions in a uniform manner.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.