B0368
Title: Post-selection inference for individualized treatment rules
Authors: Ashkan Ertefaie - University of Rochester (United States) [presenting]
Robert Strawderman - University of Rochester (United States)
Jeremiah Jones - University of Rochester (United States)
Abstract: Constructing an optimal treatment regime become complex when there is a large number of prognostic factors, such as patients genetic information, demographic characteristics, medical history over time. Existing methods only focus on selecting the important variables for the decision-making process and fall short in providing inference for the selected model. We fill this gap by leveraging the conditional selective inference methodology. We show that the proposed method is asymptotically valid given certain rate assumptions in semiparametric regression.
