Ji will discuss Bayesian statistics and their application to modern clinical trials. He will show the key differences between Bayesian designs, modeling, and analysis and p value-based traditional fixed designs. Examples including COVID-19 vaccine trials will be provided, focusing on Bayesian adaptive dose-finding designs. An important feature of Bayesian adaptive designs is the flexibility in making adaptive decisions based on trial interim data.
Speaker: Yuan Ji, PhD, Professor of Biostatistics, University of Chicago
Register: http://eepurl.com/g1X35P
Event Type