A Unified Approach to Nonparametric Comparison of Receiver Operating Characteristic Curves for Longitudinal and Clustered Data

• Published in: Journal of the American Statistical Association Vol. 103; no. 482; pp. 705 - 713
• Main Authors: Li, Gang, Zhou, Kefei
• Format: Journal Article
• Language: English
• Published: Alexandria, VA Taylor & Francis 01.06.2008; American Statistical Association; Taylor & Francis Ltd
• Subjects: Algorithms; Applications; Approximation; Area under the receiver operating characteristic curve; Asymptotic methods; Bootstrap resampling; Cluster analysis; Clustered data; Combinatorics; Combinatorics. Ordered structures; Comparative analysis; Confidence band; Confidence interval; Confidence intervals; Correlations; Density; Density estimation; Designs and configurations; Diagnostic systems; Diagnostic tests; Distribution; Estimation methods; Exact sciences and technology; Experimental design; Eyes; General topics; Glaucoma; Intersection-union tests; Longitudinal data; Longitudinal studies; Markers; Mathematics; Measurement; Medical diagnostic tests; Monte Carlo simulation; Multiple comparison; Nonparametric statistics; Paired design; Partial area under the receiver operating characteristic curve; Probability and statistics; Quantile process; Regression analysis; Repeated measurement; Sciences and techniques of general use; Significance level; Startle response; Statistical methods; Statistics; Stochastic models; Stochastic processes; Theory and Methods; Visual fields; United States > US; Density estimation; Correlation; Empirical process; Paired comparison; Statistical distribution; Cluster analysis (statistics); Non parametric estimation; Clustered data; Longitudinal data; Multivariate analysis; Stochastic method; Stochastic process; Paired design; Partial area under the receiver operating characteristic curve; Quantile process; Confidence set; Diagnostic test; Intersection-union tests; Confidence band; Distribution function; Repeated measurement; Approximation theory; Monte Carlo method; Approximate method; Roc curve; Statistical association; Statistical estimation; Multiple comparison; Joint distribution; Confidence interval; Statistical method; Statistical regression; Area under the receiver operating characteristic curve; Numerical analysis; Simulation; Correlation analysis; Experimental design; Receiver operating characteristic curves; Small sample; Application

We present a unified approach to nonparametric comparisons of receiver operating characteristic (ROC) curves for a paired design with clustered data. Treating empirical ROC curves as stochastic processes, their asymptotic joint distribution is derived in the presence of both between-marker and withi...