A multiple regression imputation method with application to sensitivity analysis under intermittent missingness

DOI10.1080/03610926.2020.1834581OpenAlexW3113235559MaRDI QIDQ5093703

Rolando Uranga, Geert Molenberghs, S.M.Allende-Alonso

Publication date: 1 August 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2020.1834581

zbMATH Keywords

sensitivity analysisGibbs samplerclinical trialmissing datamultiple imputation

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• SAS

Cites Work

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• Models for discrete longitudinal data.
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Inference and missing data
• Multiple Imputation and its Application
• Proper and Improper Multiple Imputation
• Informative Drop-Out in Longitudinal Data Analysis
• Monte Carlo sampling methods using Markov chains and their applications
• Clinical Trials with Missing Data
• Linear mixed models for longitudinal data

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