Efficient Adaptive Randomization and Stopping Rules in Multi-arm Clinical Trials for Testing a New Treatment

DOI10.1080/07474946.2012.719433zbMath1293.62162OpenAlexW2028413486WikidataQ35766576 ScholiaQ35766576MaRDI QIDQ4650223

Tze Leung Lai, Olivia Yueh-Wen Liao

Publication date: 27 November 2012

Published in: Sequential Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4476492

zbMATH Keywords

information boundadaptive allocationinterim analysismultiple treatmentinternal pilotmulti-armed bandit theory

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Sequential statistical analysis (62L10) Statistical ranking and selection procedures (62F07)

Related Items (1)

Bandit Theory: Applications to Learning Healthcare Systems and Clinical Trials

Cites Work

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• Adaptive treatment allocation and the multi-armed bandit problem
• Asymptotic optimality of invariant sequential probability ratio tests
• 2-SPRT's and the modified Kiefer-Weiss problem of minimizing an expected sample size
• Sequential Methods in Multi-Arm Clinical Trials
• Lower Bounds for the Expected Sample Size and the Average Risk of a Sequential Procedure
• Power, sample size and adaptation considerations in the design of group sequential clinical trials
• Sequential Generalized Likelihood Ratios and Adaptive Treatment Allocation for Optimal Sequential Selection
• Some aspects of the sequential design of experiments

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