Biometrika Advance Access originally published online on April 1, 2009
Biometrika 2009 96(2):371-382; doi:10.1093/biomet/asp002
Article |
Adjusting for covariate effects on classification accuracy using the covariate-adjusted receiver operating characteristic curve
Division of Public Health Sciences, Fred Hutchinson Cancer, Research Center, 1100 Fairview Avenue North, Seattle, Washington 98109, U.S.A. hjanes{at}scharp.org mspepe{at}u.washington.edu
Received for publication 1 May 2007. Revision received 1 June 2008.
Recent scientific and technological innovations have produced an abundance of potential markers that are being investigated for their use in disease screening and diagnosis. In evaluating these markers, it is often necessary to account for covariates associated with the marker of interest. Covariates may include subject characteristics, expertise of the test operator, test procedures or aspects of specimen handling. In this paper, we propose the covariate-adjusted receiver operating characteristic curve, a measure of covariate-adjusted classification accuracy. Nonparametric and semiparametric estimators are proposed, asymptotic distribution theory is provided and finite sample performance is investigated. For illustration we characterize the age-adjusted discriminatory accuracy of prostate-specific antigen as a biomarker for prostate cancer.
Key Words: Classification accuracy • Covariate effect • Receiver operating characteristic curve • Sensitivity • Specificity
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