Online Program Home
My Program

Abstract Details

Activity Number: 28
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #319209
Title: A Subgroup Identification Method Based on Quantitative Criteria
Author(s): Yan Sun* and Samad Hedayat
Companies: AbbVie and University of Illinois at Chicago
Keywords: precision medicine ; subgroup identification

Statistical learning methods of subgroup identification based on interaction effect are of great interest in the pharmaceutical area. It is desirable to find a subgroup of patients with enhanced treatment effect so that we can efficiently lower the sample size and improve the success rate of drug development projects. Most of the current subgroup identification methods are either optimized for prediction or based on some qualitative criteria. In this presentation, we propose a method called "SQUANT" that integrates the quantitative information into subgroup identification. The new method does not rely on any specific parametric model, and works for continuous, binary and survival response. We will also demonstrate the performance of the proposed method through simulation.

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

Back to the full JSM 2016 program

Copyright © American Statistical Association