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A weighted Wilcoxon estimate for the covariate-specific ROC curve

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Abstract

The covariate-specific receiver operating characteristic (ROC) curve is an important tool for evaluating the classification accuracy of a diagnostic test when it is associated with certain covariates. In this paper, a weighted Wilcoxon estimator is constructed for estimating this curve under the framework of location-scale model for the test result. The asymptotic normality is established, both for the regression parameter estimator and the estimator for the covariate-specific ROC curve at a fixed false positive point. Simulation results show that the Wilcoxon estimator compares favorably to its main competitors in terms of the standard error, especially when outliers exist in the covariates. As an illustration, the new procedure is applied to the dementia data from the national Alzheimer’s coordinating center.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 11401561 and 11301031). The authors thank two referees for their valuable suggestions, and the National Alzheimer’s Coordinating Center for providing the data for analysis (the interpretation and reporting of the data are the sole responsibility of the authors).

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Authors and Affiliations

  1. School of Economics and Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, 361005, China

    QingZhao Zhang

  2. Department of Statistics, Beijing Normal University, Beijing, 100875, China

    XiaoGang Duan

  3. Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA

    XiaoHua Zhou

Authors
  1. QingZhao Zhang
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  2. XiaoGang Duan
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  3. XiaoHua Zhou
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Correspondence to XiaoHua Zhou.

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Zhang, Q., Duan, X. & Zhou, X. A weighted Wilcoxon estimate for the covariate-specific ROC curve. Sci. China Math. 60, 1705–1716 (2017). https://doi.org/10.1007/s11425-015-0158-0

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  • DOI: https://doi.org/10.1007/s11425-015-0158-0

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