Open AccessSemiparametric single-index model for estimating optimal individualized treatment strategy
Author(s) -
Rui Song,
Shuyi Luo,
Donglin Zeng,
Hao Helen Zhang,
Wenbin Lu,
Zhiguo Li
Publication year - 2017
Publication title -
electronic journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.482
H-Index - 54
ISSN - 1935-7524
DOI - 10.1214/17-ejs1226
Subject(s) - covariate , mathematics , nonparametric statistics , estimator , single index model , personalized medicine , semiparametric regression , semiparametric model , index (typography) , monotone polygon , mathematical optimization , econometrics , statistics , computer science , bioinformatics , geometry , world wide web , biology
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