A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data With Application to the Breast Cancer Prevention Trial

DOI10.1198/JASA.2010.AP09321zbMath1388.62336OpenAlexW1995566320WikidataQ33880852 ScholiaQ33880852MaRDI QIDQ5255675

Chenguang Wang, S. Land, Michael J. Daniels, Daniel O. Scharfstein

Publication date: 17 June 2015

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/cgi/viewcontent.cgi?article=1188&context=jhubiostat

zbMATH Keywords

prior elicitation informative drop-out cancer prevention intermittent missing ness

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 (8)

Bayesian methods for dealing with missing data problems ⋮ A Bayesian data combination approach for repeated durations under unobserved missing indicators: application to interpurchase-timing in marketing ⋮ Frequency coverage properties of a uniform shrinkage prior distribution ⋮ 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 ⋮ Fully Bayesian inference under ignorable missingness in the presence of auxiliary covariates ⋮ A Note on MAR, Identifying Restrictions, Model Comparison, and Sensitivity Analysis in Pattern Mixture Models with and without Covariates for Incomplete Data

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