Adjusting for covariate effects on classification accuracy using the covariate-adjusted receiver operating characteristic curve

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. Covariate...

Full description

Saved in:
Bibliographic Details
Published inBiometrika Vol. 96; no. 2; pp. 371 - 382
Main Authors Janes, Holly, Pepe, Margaret S
Format Journal Article
LanguageEnglish
Published England Oxford University Press for Biometrika Trust 01.06.2009
SeriesBiometrika
Online AccessGet more information

Cover

Loading…
More Information
Summary: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.
ISSN:0006-3444
1464-3510
DOI:10.1093/biomet/asp002