Modeling heterogeneity in the assessment of treatment effects on tumor development while accounting for monotone dropout

DOI10.1007/S40840-021-01225-5zbMath1496.62181OpenAlexW4210766211MaRDI QIDQ2089348

Shi Zhang, Zhenhuan Wu, Wenzhuan Zhang, Xing-De Duan

Publication date: 6 October 2022

Published in: Bulletin of the Malaysian Mathematical Sciences Society. Second Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s40840-021-01225-5

zbMATH Keywords

random effects modelsclustered datamissing databest linear unbiased predictorTweedie family

Mathematics Subject Classification ID

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

Cites Work

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• Modeling the Drop-Out Mechanism in Repeated-Measures Studies
• Nested Generalized Linear Mixed Models: An Orthodox Best Linear Unbiased Predictor Approach
• Bayesian Dose-Finding in Two Treatment Cycles Based on the Joint Utility of Efficacy and Toxicity

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