Improving the performance of Bayesian logistic regression model with overdose control in oncology dose‐finding studies
Author:
Affiliation:
1. Merck & Co., Inc. West Point Pennsylvania USA
2. Bristol Myers Squibb Berkeley Heights New Jersey USA
3. Global Biometrics and Data Sciences Bristol Myers Squibb Boudry Switzerland
Publisher
Wiley
Subject
Statistics and Probability,Epidemiology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.9402
Reference28 articles.
1. Bayesian optimal interval designs for phase I clinical trials
2. A modified toxicity probability interval method for dose-finding trials
3. A Bayesian interval dose-finding design addressingOckham's razor: mTPI-2
4. Continual Reassessment Method: A Practical Design for Phase 1 Clinical Trials in Cancer
5. Critical aspects of the Bayesian approach to phase I cancer trials
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1. Adaptively leveraging external data with robust meta‐analytical‐predictive prior using empirical Bayes;Pharmaceutical Statistics;2023-05-23
2. “Improving the performance of Bayesian logistic regression model with overdose control in oncology dose‐finding studies” by Hongtao Zhang, Alan Chiang, and Jixian Wang;Statistics in Medicine;2022-11-17
3. Explicit underdose control based on toxicity: Four points to consider;Statistics in Medicine;2022-11-17
4. Comparison of Bayesian and Classical Methods for Exploring the Important Factors regarding Maternal and Child Health Care;Mathematical Problems in Engineering;2022-10-11
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