title: A Bayesian sequential design with binary outcome.
abstract: Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha-spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maximum total sample size on critical values. Alpha-spending functions are compared using power and actual sample size through simulations. Further simulations show that, when total sample size is fixed, the proposed design has greater power than the traditional Bayesian sequential design, which sets equal stopping bounds at all interim analyses. We also find that the proposed design with the new stopping for futility rule results in greater power and can stop earlier with a smaller actual sample size, compared with the traditional stopping rule for futility when all other conditions are held constant. Finally, we apply the proposed method to a real data set and compare the results with traditional designs.
authors.affiliation: Pharmaceutical Product Development, LLC., Austin, TX, USA.
authors.forename: Han
authors.initials: H
authors.lastname: Zhu
authors.affiliation: Biostatistics Program, School of Public Health, LSUHSC, New Orleans, LA, USA.
authors.forename: Qingzhao
authors.identifier: 0000-0001-8194-0798
authors.initials: Q
authors.lastname: Yu
authors.affiliation: Biostatistics Program, School of Public Health, LSUHSC, New Orleans, LA, USA.
authors.forename: Donald E
authors.initials: DE
authors.lastname: Mercante
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D012107:Research Design; D018401:Sample Size
keywords: Bayesian clinical trial; alpha-spending functions; sequential design; stop for futility