title: Jackknife variance of the partial area under the empirical receiver operating characteristic curve.
abstract: Receiver operating characteristic analysis provides an important methodology for assessing traditional (e.g., imaging technologies and clinical practices) and new (e.g., genomic studies, biomarker development) diagnostic problems. The area under the clinically/practically relevant part of the receiver operating characteristic curve (partial area or partial area under the receiver operating characteristic curve) is an important performance index summarizing diagnostic accuracy at multiple operating points (decision thresholds) that are relevant to actual clinical practice. A robust estimate of the partial area under the receiver operating characteristic curve is provided by the area under the corresponding part of the empirical receiver operating characteristic curve. We derive a closed-form expression for the jackknife variance of the partial area under the empirical receiver operating characteristic curve. Using the derived analytical expression, we investigate the differences between the jackknife variance and a conventional variance estimator. The relative properties in finite samples are demonstrated in a simulation study. The developed formula enables an easy way to estimate the variance of the empirical partial area under the receiver operating characteristic curve, thereby substantially reducing the computation burden, and provides important insight into the structure of the variability. We demonstrate that when compared with the conventional approach, the jackknife variance has substantially smaller bias, and leads to a more appropriate type I error rate of the Wald-type test. The use of the jackknife variance is illustrated in the analysis of a data set from a diagnostic imaging study.
authors.affiliation: 1 Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Andriy I
authors.initials: AI
authors.lastname: Bandos
authors.affiliation: 1 Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Ben
authors.initials: B
authors.lastname: Guo
authors.affiliation: 2 Department of Radiology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: David
authors.initials: D
authors.lastname: Gur
mesh_terms: D000704:Analysis of Variance; D019540:Area Under Curve; D056808:Biostatistics / Q000379:methods; D003198:Computer Simulation; D003955:Diagnostic Tests, Routine / Q000706:statistics & numerical data; D006801:Humans; D012372:ROC Curve; D018709:Statistics, Nonparametric
keywords: Jackknife; ROC analysis; closed-form; nonparametric estimation; partial AUC