Semiparametric Single-Index Model for Estimating Optimal Individualized Treatment Strategy.

TitleSemiparametric Single-Index Model for Estimating Optimal Individualized Treatment Strategy.
Publication TypeJournal Article
Year of Publication2017
AuthorsSong, Rui, Shikai Luo, Donglin Zeng, Hao Helen Zhang, Wenbin Lu, and Zhiguo Li
JournalElectron J Stat
Volume11
Issue1
Pagination364-384
Date Published2017
ISSN1935-7524
Abstract

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.

DOI10.1214/17-EJS1226
Alternate JournalElectron J Stat
Original PublicationSemiparametric single-index model for estimating optimal individualized treatment strategy.
PubMed ID28959371
PubMed Central IDPMC5612500
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 GM047845 / GM / NIGMS NIH HHS / United States
R01 NS073671 / NS / NINDS NIH HHS / United States
U01 NS082062 / NS / NINDS NIH HHS / United States