Variable Selection for Qualitative Interactions in Personalized Medicine While Controlling the Family-Wise Error Rate

摘要: For many years, subset analysis has been a popular topic for the biostatistics and clinical trials literature. In more recent discussion focused on finding subsets of genomes which play role in effect treatment, often referred to as stratified or personalized medicine. Though highly sought after, methods detecting with altering treatment effects are limited lacking power. this article we discuss variable selection qualitative interactions aim discover these critical patient subsets. We propose new technique designed specifically find interaction variables among large set while still controlling number false discoveries. compare method against standard tests using simulations give an example its use data from randomized controlled trial depression.