C M Rutter1. 1. Group Health Cooperative of Puget Sound, Center for Health Studies, Seattle, WA 98101, USA.
Abstract
RATIONALE AND OBJECTIVES: The purpose of this study was to describe a simple bootstrap approach for estimating sensitivity, specificity, and the area under the receiver operating characteristic curve for multisite test outcome data. MATERIALS AND METHODS: The performance of bootstrap estimates was evaluated and compared with that of analytic estimates by using a simulation study. Bootstrapping was demonstrated by using data from a previous study comparing two angiographic methods. RESULTS: Analytic and bootstrap estimates had similar coverage rates for 95% confidence intervals. With many sites per patient, bootstrap estimates had slightly better coverage than analytic estimates. Bootstrap percentile intervals had better coverage than asymptotic normal bootstrap intervals. CONCLUSION: Bootstrapping is a useful method of estimating confidence intervals for the area under the receiver operating characteristic curve, sensitivity, and specificity when data are correlated.
RATIONALE AND OBJECTIVES: The purpose of this study was to describe a simple bootstrap approach for estimating sensitivity, specificity, and the area under the receiver operating characteristic curve for multisite test outcome data. MATERIALS AND METHODS: The performance of bootstrap estimates was evaluated and compared with that of analytic estimates by using a simulation study. Bootstrapping was demonstrated by using data from a previous study comparing two angiographic methods. RESULTS: Analytic and bootstrap estimates had similar coverage rates for 95% confidence intervals. With many sites per patient, bootstrap estimates had slightly better coverage than analytic estimates. Bootstrap percentile intervals had better coverage than asymptotic normal bootstrap intervals. CONCLUSION: Bootstrapping is a useful method of estimating confidence intervals for the area under the receiver operating characteristic curve, sensitivity, and specificity when data are correlated.
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