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Proceedings Paper

Statistical issues in ROC curve analysis
Author(s): Howard E. Rockette; Nancy A. Obuchowski; Charles E. Metz; David Gur
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Paper Abstract

Using simulation studies and the data obtained from our clinical investigations, we are comparing some of the techniques commonly employed in ROC analysis. The general areas of our investigation include estimation of the area under the ROC curve and its associated standard error, comparison of the areas under two ROC curves, and simultaneous comparison of the areas under more than two ROC curves. For single ROC curves, maximum likelihood estimation based on the binormal model is being compared to the approximate area obtained using the Wilcoxon Statistic. Standard errors obtained from classical asymptotic theory are being evaluated and compared to standard errors based on jackknifing. With regard to the task of assessing differences in the diagnostic accuracies of two systems, our investigations have compared the maximum likelihood estimation method to a nonparametric method based on the Wilcoxon Statistic, focusing primarily on correlated observations, e.g., from readings of different modalities' images of the same patients. Extensions of existing methodology to the problem of comparing ROC areas from more than two modalities are being addressed as well as problems associated with the incorporation of multiple readers.

Paper Details

Date Published: 1 August 1990
PDF: 9 pages
Proc. SPIE 1234, Medical Imaging IV: PACS Systems Design and Evaluation, (1 August 1990); doi: 10.1117/12.18951
Show Author Affiliations
Howard E. Rockette, Univ. of Pittsburgh School of Medicine (United States)
Nancy A. Obuchowski, Univ. of Pittsburgh School of Medicine (United States)
Charles E. Metz, Univ. of Chicago (United States)
David Gur, Univ. of Pittsburgh School of Medicine (United States)


Published in SPIE Proceedings Vol. 1234:
Medical Imaging IV: PACS Systems Design and Evaluation
Samuel J. Dwyer; R. Gilbert Jost, Editor(s)

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