A DIRECT SEMIPARAMETRIC RECEIVER OPERATING CHARACTERISTIC CURVE REGRESSION WITH UNKNOWN LINK AND BASELINE FUNCTIONS

被引:12
作者
Lin, Huazhen [1 ]
Zhou, Xiao-Hua [2 ,3 ,4 ]
Li, Gang [5 ]
机构
[1] SW Univ Finance & Econ, Sch Stat, Chengdu 611130, Peoples R China
[2] VA Puget Sound Hlth Care Syst, HSR&D Ctr Excellence, Seattle, WA 98108 USA
[3] Univ Washington, Dept Biostat, Seattle, WA 98195 USA
[4] Peking Univ, Beijing Int Ctr Math Res, Beijing 100871, Peoples R China
[5] Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA 90095 USA
基金
中国国家自然科学基金; 国家杰出青年科学基金;
关键词
Diagnostic tests; kernel smoothing; nonparametric; ROC regression; transformation models; OPTIMUM KERNEL ESTIMATORS; LIKELIHOOD-ESTIMATION; TRANSFORMATION; MODEL;
D O I
10.5705/ss.2010.167
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this article, we study a direct receiver operating characteristic (ROC) curve regression model with completely unknown link and baseline functions. A semiparametric procedure is proposed to estimate both the parametric and nonparametric components of the model. The resulting parameter estimates and ROC curve estimates are shown to be consistent, and asymptotically normal with a n(-1/2) convergence rate. With arbitrary link and baseline functions, our model is more robust than existing direct ROC regression models that require either complete or partially complete specification of the link and baseline functions. Moreover, the robustness of our new method is gained at little cost to efficiency, as evidenced by the parametric convergence rate of our estimators and by the simulation study. An illustrative example is given using a hearing test data set.
引用
收藏
页码:1427 / 1456
页数:30
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