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Activity Number: 165
Type: Topic Contributed
Date/Time: Monday, August 1, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #320981
Title: Identifying Interactions Using Convex Optimization
Author(s): Jacob Bien* and Robert Tibshirani and Noah Simon
Companies: Cornell University and Stanford University and University of Washington
Keywords: interactions ; sparsity ; high-dimensional ; convexity

We consider the testing of all pairwise interactions in a two-class problem with many features. We devise a hierarchical testing framework that considers an interaction only when one or more of its constituent features has a nonzero main effect. The test is based on a convex optimization framework that seamlessly considers main effects and interactions together. We show---both in simulation and on a genomic data set from the SAPPHIRe study---a potential gain in power and interpretability over a standard (nonhierarchical) interaction test.

Authors who are presenting talks have a * after their name.

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