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2017 Semiparametric single-index model for estimating optimal individualized treatment strategy
Rui Song, Shikai Luo, Donglin Zeng, Hao Helen Zhang, Wenbin Lu, Zhiguo Li
Electron. J. Statist. 11(1): 364-384 (2017). DOI: 10.1214/17-EJS1226

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.

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Rui Song. Shikai Luo. Donglin Zeng. Hao Helen Zhang. Wenbin Lu. Zhiguo Li. "Semiparametric single-index model for estimating optimal individualized treatment strategy." Electron. J. Statist. 11 (1) 364 - 384, 2017. https://doi.org/10.1214/17-EJS1226

Information

Received: 1 February 2016; Published: 2017
First available in Project Euclid: 13 February 2017

zbMATH: 1356.62220
MathSciNet: MR3608677
Digital Object Identifier: 10.1214/17-EJS1226

Subjects:
Primary: 62G05
Secondary: 62G99

JOURNAL ARTICLE
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Vol.11 • No. 1 • 2017
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