About this episode

The episode discusses the differences and similarities between Bayesian and frequentist statistical approaches in clinical trials.

In this episode of Communicable , Emily McDonald and Josh Davis are joined by Roger Lewis (USA) and Ian Marschner (Australia) to compare and contrast Bayesian and frequentist statistical approaches. The panel discusses the fundamental principles of both methods, common misconceptions, and the extent to which they are often more similar than many realise. Together, they explore their use in clinical trial design, analysis, and reporting, including adaptive trials and sequential learning. Additional topics include sample size misconceptions, regulatory versus clinical thresholds, and the challenges of interpreting post hoc reanalyses of negative trials. This episode was edited by Kathryn Hostettler and the executive producer of Communicable is Angela Huttner. Further reading: Berry SM, et al. Bayesian Adaptive Methods for Clinical Trials (Chapman & Hall/CRC Biostatistics Series). Boca Raton (FL): CRC Press; 2010. FDA Guidance Document: Use of Bayesian Methodology in Clinical Trials of Drug and Biological Products FDA, 2026, https://www.fda.gov/regulatory-information/search-fda-guidance-documents/use-bayesian-methodology-clinical-trials-drug-and-biological-products Lee TC, et…

People in this episode

Hosts: Emily McDonald, Josh Davis

Guests: Roger Lewis, Ian Marschner

Topics covered

• Bayesian statistics
• frequentist statistics
• clinical trial design
• statistical analysis
• sample size misconceptions
• regulatory thresholds

Keywords

• Bayesian
• frequentist
• clinical trials
• statistical methods
• adaptive trials
• sequential learning
• post hoc reanalyses

Mentioned in this episode

Organizations: CMI Communications, FDA

Books & works: Bayesian Adaptive Methods for Clinical Trials, JAMA Guide to Statistics and Methods

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