# 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} }

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

#### References

##### Publications referenced by this paper.

SHOWING 1-10 OF 47 REFERENCES

Selection of the effect size for sample size determination for a continuous response in a superiority clinical trial using a hybrid classical and Bayesian procedure

- Mathematics, Medicine
- 2016

10

Selection of the treatment effect for sample size determination in a superiority clinical trial using a hybrid classical and Bayesian procedure.

- Mathematics, Medicine
- 2015

6

A hybrid Bayesian-frequentist approach to evaluate clinical trial designs for tests of superiority and non-inferiority.

- Medicine, Mathematics
- 2008

10

An Extension of Bayesian Expected Power and Its Application in Decision Making

- Medicine, Mathematics
- 2010

9

Bayesian sample size calculations for a non-inferiority test of two proportions in clinical trials.

- Mathematics, Medicine
- 2008

10

From statistical power to statistical assurance: It's time for a paradigm change in clinical trial design

- Computer Science, Mathematics
- 2017

5