title: Bayesian designs and the control of frequentist characteristics: a practical solution.
abstract: Frequentist concepts, such as the control of the type I error or the false discovery rate, are well established in the medical literature and often required by regulators. Most Bayesian designs are defined without explicit considerations of frequentist characteristics. Once the Bayesian design is structured, statisticians use simulations and adjust tuning parameters to comply with a set of targeted operating characteristics. These adjustments affect the use of prior information and utility functions. Here we consider a Bayesian decision theoretic approach for experimental designs with explicit frequentist requisites. We define optimal designs under a set of constraints required by a regulator. Our approach combines the use of interpretable utility functions with frequentist criteria, and selects an optimal design that satisfies a set of required operating characteristics. We illustrate the approach using a group-sequential multi-arm Phase II trial and a bridging trial.
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Department of Biostatistics Harvard School of Public Health, Boston, Massachusetts, 02115, U.S.A.
authors.forename: Steffen
authors.initials: S
authors.lastname: Ventz
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Department of Biostatistics Harvard School of Public Health, Boston, Massachusetts, 02115, U.S.A.
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Trippa
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001699:Biometry / Q000379:methods*; D002986:Clinical Trials as Topic / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results; D012107:Research Design; D012680:Sensitivity and Specificity
keywords: Bayesian design; Clinical trials; Decision theory; Frequentist constraints