Fully Bayesian inference under ignorable missingness in the presence of auxiliary covariates

DOI10.1111/biom.12121zbMath1419.62333OpenAlexW1558305862WikidataQ33555560 ScholiaQ33555560MaRDI QIDQ4979228

Chenguang Wang, Bess H. Marcus, Michael J. Daniels

Publication date: 17 June 2014

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4007313

zbMATH Keywords

multiple imputationmarginalized modelsauxiliary variable MARcongenial imputation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Generalized linear models (logistic models) (62J12)

Related Items (5)

Statistical inference for nonignorable missing-data problems: a selective review ⋮ Bayesian methods for dealing with missing data problems ⋮ Bayesian Nonparametrics for Missing Data in Longitudinal Clinical Trials ⋮ Bayesian approaches for missing not at random outcome data: the role of identifying restrictions ⋮ A Semiparametric Bayesian Approach to Dropout in Longitudinal Studies With Auxiliary Covariates

Cites Work

• Unnamed Item
• Unnamed Item
• Marginalized Transition Models and Likelihood Inference for Longitudinal Categorical Data
• Missing data imputation using the multivariate \(t\) distribution
• Spike and slab variable selection: frequentist and Bayesian strategies
• A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times
• Missing Data in Longitudinal Studies
• Inference and missing data
• Bayesian Effect Estimation Accounting for Adjustment Uncertainty
• A prior for the variance in hierarchical models
• A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data With Application to the Breast Cancer Prevention Trial
• Multiple imputation: current perspectives

This page was built for publication: Fully Bayesian inference under ignorable missingness in the presence of auxiliary covariates