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Activity Number: 464 - New Directions in Personalized Treatment Selection
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
Sponsor: International Indian Statistical Association
Abstract #329398 Presentation
Title: Selection of the Optimal Personalized Treatment from Multiple Treatments with Multivariate Outcome Measures
Author(s): Somnath Datta* and Chathura Siriwardhana and Karunarathna B Kulasekera
Companies: University of Florida and University of Hawaii and University of Louisville
Keywords: Design variables; Personalized Treatments; Single Index Models; Rank Aggregation

We propose a novel method for individualized treatment selection when the treatment response is multivariate. For the K treatment (K ? 2) scenario we compare quantities that are suitable indexes based on outcome variables for each treatment conditional on patient speci?c scores constructed from collected covariate measurements. Our method covers any number of treatments and out-come variables, and it can be applied for a broad set of models. The proposed method uses a rank aggregation technique to estimate an ordering of treatments based on ranked lists of treatment performance measures such as smooth conditional means and conditional probability of a response for one treatment dominating others. The method has the ?exibility to incorporate patient and clinician heterogeneities to the optimal treatment decision on an individual case basis. An empirical study demonstrates the performance of the proposed method in ?nite samples. We also present a data analysis using a HIV clinical trial data to show the applicability of the proposed procedure for real data.

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

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