title: Subgroup finding via Bayesian additive regression trees.
abstract: We provide a Bayesian decision theoretic approach to finding subgroups that have elevated treatment effects. Our approach separates the modeling of the response variable from the task of subgroup finding and allows a flexible modeling of the response variable irrespective of potential subgroups of interest. We use Bayesian additive regression trees to model the response variable and use a utility function defined in terms of a candidate subgroup and the predicted response for that subgroup. Subgroups are identified by maximizing the expected utility where the expectation is taken with respect to the posterior predictive distribution of the response, and the maximization is carried out over an a priori specified set of candidate subgroups. Our approach allows subgroups based on both quantitative and categorical covariates. We illustrate the approach using simulated data set study and a real data set. Copyright © 2017 John Wiley & Sons, Ltd.
authors.affiliation: University of Cincinnati, Cincinnati, OH, U.S.A.
authors.forename: Siva
authors.identifier: 0000-0001-7093-8078
authors.initials: S
authors.lastname: Sivaganesan
authors.affiliation: University of Texas at Austin, Austin, TX, U.S.A.
authors.forename: Peter
authors.initials: P
authors.lastname: Müller
authors.affiliation: Cincinnati Children Hospital and Medical Center, Cincinnati, OH, U.S.A.
authors.forename: Bin
authors.initials: B
authors.lastname: Huang
mesh_terms: D000293:Adolescent; D001171:Arthritis, Juvenile / Q000178:diet therapy / Q000503:physiopathology; D001499:Bayes Theorem; D056808:Biostatistics; D015519:Bone Density / Q000187:drug effects; D002136:Calcium, Dietary / Q000008:administration & dosage; D002648:Child; D003198:Computer Simulation; D003662:Decision Theory; D019587:Dietary Supplements; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012044:Regression Analysis; D016896:Treatment Outcome
chemical_list: D002136:Calcium, Dietary
keywords: Bayesian analysis; subgroup analysis; utility