A Sensitivity Analysis for Shared-Parameter Models for Incomplete Longitudinal Outcomes

DOI10.1002/bimj.200800235zbMath1207.62199OpenAlexW1969121400WikidataQ42640717 ScholiaQ42640717MaRDI QIDQ2786156

Geert Verbeke, Marc Aerts, Michael G. Kenward, Geert Molenberghs, An Creemers, Niel Hens

Publication date: 21 September 2010

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1942/10817

zbMATH Keywords

missing at randommissing not at randomselection modelpattern-mixture modelonychomychosis

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50)

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Cites Work

• Unnamed Item
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• Kernel weighted influence measures
• The nature of sensitivity in monotone missing not at random models
• Models for discrete longitudinal data.
• Estimation and comparison of Changes in the Presence of Informative Right Censoring: Conditional Linear Model
• Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process
• Every Missingness not at Random Model Has a Missingness at Random Counterpart with Equal Fit
• Inference and missing data
• Monotone missing data and pattern‐mixture models
• A class of pattern-mixture models for normal incomplete data
• Pattern-Mixture Models for Multivariate Incomplete Data
• An Approximate Generalized Linear Model with Random Effects for Informative Missing Data
• Modeling the Drop-Out Mechanism in Repeated-Measures Studies
• Strategies to fit pattern-mixture models
• Analyzing incomplete longitudinal clinical trial data