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Activity Number: 536 - Advanced Bayesian Methods for Modern Clinical Trials
Type: Invited
Date/Time: Thursday, August 11, 2022 : 10:30 AM to 12:20 PM
Sponsor: International Society for Bayesian Analysis (ISBA)
Abstract #320467
Title: On Bayesian Sequential Clinical Trial Designs
Author(s): Tianjian Zhou* and Yuan Ji
Companies: Colorado State University and The University of Chicago
Keywords: Adaptive design; Interim analysis; Likelihood principle; Multiplicity; Optional stopping; Sequential hypothesis testing

Clinical trials usually involve sequential patient entry. When designing a clinical trial, it is often desirable to include a provision for interim analyses of accumulating data with the potential for stopping the trial early. We review Bayesian sequential clinical trial designs based on posterior probabilities, posterior predictive probabilities, and decision-theoretic frameworks. A pertinent question is whether Bayesian sequential designs need to be adjusted for the planning of interim analyses. We answer this question from three perspectives: a frequentist-oriented Bayesian perspective, a calibrated Bayesian perspective, and a subjective Bayesian perspective. We also provide new insights into the likelihood principle, which is commonly tied with statistical inference and decision making in sequential clinical trials. Some theoretical results are derived, and numerical studies are conducted to illustrate and assess these designs.

Authors who are presenting talks have a * after their name.

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