Selection and combination of biomarkers using ROC method for disease classification and prediction |
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| Authors: | Huazhen Lin Ling Zhou Heng Peng Xiao‐Hua Zhou |
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| Affiliation: | 1. School of Statistics, Southwestern University of Finance and Economics, Chengdu, Sichuan 611130, China;2. School of Mathematics, Sichuan University, Chengdu, Sichuan 610064, P.R. China;3. Department of Mathematics, Hong Kong Baptist University, Hong Kong, P.R. China;4. Department of Biostatistics, Harbin Medical University, Harbin, China;5. Department of Biostatistics, University of Washington, Seattle, WA 98195, USA |
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| Abstract: | Based on the SCAD penalty and the area under the ROC curve (AUC), we propose a new method for selecting and combining biomarkers for disease classification and prediction. The proposed estimator for the combination of the biomarkers has an oracle property; that is, the estimated combination of the biomarkers performs as well as it would have been if the biomarkers significantly associated with the outcome had been known in advance, in terms of discriminative power. The proposed estimator is computationally feasible, n1/2‐consistent and asymptotically normal. Simulation studies show that the proposed method performs better than existing methods. We illustrate the proposed methodology in the acoustic startle response study. The Canadian Journal of Statistics 39: 324–343; 2011 © 2011 Statistical Society of Canada |
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| Keywords: | Generalized linear model SCAD penalty ROC curve selection and combination of biomarker MSC 2010: Primary 62H30 secondary 62P10 |
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