Sample Size Calculations for Bayesian Clinical Studies
Tuesday, April 29, 2025, 10 - 11am
Location: Room 740 @ Health Sciences building
Registration Link: https://docs.google.com/forms/d/e/1FAIpQLScOZDvITeszoAmkhmAtpDtvoJgt9rMoQTTdBnrndlOyVRXXrg/viewform

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Description

Instructor: Luke Hagar

Regulatory agencies like Health Canada require that researchers report the probabilities of making incorrect decisions in clinical studies, such as the probability of incorrectly concluding a new, superior treatment is not better than a placebo. Some of these probabilities are controlled by choosing sample sizes for the study. In Bayesian studies, the probabilities of making incorrect decisions must be estimated using intensive simulation. In this workshop, we discuss strategies to efficiently choose sample sizes via simulation. We will apply these methods to a simple example and describe how they can be extended to more complex settings.

Luke Hagar is a Postdoctoral Scholar in the Department of Epidemiology, Biostatistics and Occupational Health at McGill University. He recently completed a PhD in Statistics at the University of Waterloo. His research leverages theory to make simulation-based methods for experimental design more economical. He is an active member of the Statistical Society of Canada and encourages students to get involved with the CSSC and SARGC.