In this webinar, we will explore the characteristics of Bayesian sample size determination, discuss how credible intervals can be used as a Bayesian alternative to confidence intervals and how a consensus-based approach can be used to deal with the issue of differing priors.
Bayesian analysis is becoming a more and more popular form of sample size determination for clinical trials. This is because Bayesian Statistics offers the ability to integrate domain knowledge and prior study data in order to improve the efficiency and accuracy of testing and estimations. When used appropriately, this can offer many benefits over traditional frequentist methods.
We will also explore how the Bayesian Poster Error approach and Bayes Factors can be used for hypothesis testing.