Bayesian designs and the control of frequentist characteristics: A practical solution

Steffen Ventz, Lorenzo Trippa

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)218-226
Number of pages9
Issue number1
StatePublished - Mar 1 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014, The International Biometric Society.


  • Bayesian design
  • Clinical trials
  • Decision theory
  • Frequentist constraints


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