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A Clustering Method To Identify Who Benefits Most From The Treatment Group In Clinical Trials, Beom S. Lee, Pranab K. Sen, Nan Park, Roger A. Boothroyd, Roger H. Peters, David A. Chiriboga

Mental Health Law & Policy Faculty Publications

In randomized controlled trials (RCTs), the most compelling need is to determine whether the treatment condition was more effective than control. However, it is generally recognized that not all participants in the treatment group of most clinical trials benefit equally. While subgroup analyses are often used to compare treatment effectiveness across pre-determined subgroups categorized by patient characteristics, methods to empirically identify naturally occurring clusters of persons who benefit most from the treatment group have rarely been implemented. This article provides a modeling framework to accomplish this important task. Utilizing information about individuals from the treatment group who had poor outcomes, …