Modeling heterogeneity in the assessment of treatment effects on tumor development while accounting for monotone dropout
From MaRDI portal
Publication:2089348
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
Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)
Cites Work
- Unnamed Item
- Unnamed Item
- A class of pattern-mixture models for normal incomplete data
- Random effects Cox models: A Poisson modelling approach
- Pattern-Mixture Models for Multivariate Incomplete Data
- 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
This page was built for publication: Modeling heterogeneity in the assessment of treatment effects on tumor development while accounting for monotone dropout