Rui Song ColloquiumThursday, September 15, 2016 - 2:45pm
Statistics Department Colloquium
Where: LeConte College, Room 210
Speaker: Rui Song
Affiliation: North Carolina State University, Department of Statistics
Title: Minimax-Angle Learning for Optimal Treatment Decision with Heterogeneous Data
Abstract: A saline feature of data from clinical trials and medical studies is inhomogeneity. Patients not only differ in baseline characteristics, but also the way they respond to treatment. Optimal individualized treatment regimes are developed to select effective treatments based on patient’s heterogeneities. However, the optimal treatment regime might also vary for patients across different subgroups. We propose a new minimax-angle learning for estimating a single treatment decision rule that works reliably for patients across different subgroups. Based on estimated optimal treatment regimes for all subgroups, the proposed minimax-angle treatment regime is obtained by solving a quadratically constrained linear programming (QCLP), which can be efficiently computed by interior-point methods. Consistency and asymptotic normality of the estimator is established. In addition, we study the limiting distribution of the estimated value function under the obtained minimax-angle treatment regime. Numerical examples show the reliability of our novel methodology.