Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

Selection and combination of biomarkers using ROC method for disease classification and prediction

Language

English

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.© 2011 Statistical Society of Canada.

Keywords

Generalized linear model, ROC curve, SCAD penalty, Selection and combination of biomarker

Publication Date

2011

Source Publication Title

Canadian Journal of Statistics

Volume

39

Issue

2

Start Page

324

End Page

343

Publisher

Wiley

DOI

10.1002/cjs.10107

Link to Publisher's Edition

http://dx.doi.org/10.1002/cjs.10107

ISSN (print)

03195724

ISSN (electronic)

1708945X

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