Semiparametric Single-Index Model for Estimating Optimal Individualized Treatment Strategy

Electron J Stat. 2017;11(1):364-384. doi: 10.1214/17-EJS1226.


Different from the standard treatment discovery framework which is used for finding single treatments for a homogenous group of patients, personalized medicine involves finding therapies that are tailored to each individual in a heterogeneous group. In this paper, we propose a new semiparametric additive single-index model for estimating individualized treatment strategy. The model assumes a flexible and nonparametric link function for the interaction between treatment and predictive covariates. We estimate the rule via monotone B-splines and establish the asymptotic properties of the estimators. Both simulations and an real data application demonstrate that the proposed method has a competitive performance.

Keywords: Personalized medicine; Semiparametric inference; Single index model.