Corpus ID: 220249701

A review of Bayesian perspectives on sample size derivation for confirmatory trials

@inproceedings{Kunzmann2020ARO,
  title={A review of Bayesian perspectives on sample size derivation for confirmatory trials},
  author={Kevin Kunzmann and M. Grayling and K. M. Lee and D. S. Robertson and K. Rufibach and J. Wason},
  year={2020}
}
  • Kevin Kunzmann, M. Grayling, +3 authors J. Wason
  • Published 2020
  • Mathematics
  • Sample size derivation is a crucial element of the planning phase of any confirmatory trial. A sample size is typically derived based on constraints on the maximal acceptable type I error rate and a minimal desired power. Here, power depends on the unknown true effect size. In practice, power is typically calculated either for the smallest relevant effect size or a likely point alternative. The former might be problematic if the minimal relevant effect is close to the null, thus requiring an… CONTINUE READING

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