Johann Gagnon-Bartsch

The purpose of this project is to develop novel methodology to estimate treatment effects from randomized controlled trials (RCTs), while incorporating large observational remnant data and cutting-edge machine learning prediction algorithms to improve precision. The statistical precision of effect estimates from an RCT is limited by the RCT's sample size, which itself is typically subject to a number of practical constraints, such as cost. In many cases, RCT estimates may be too imprecise to...