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Biostatistics Advance Access originally published online on January 18, 2008
Biostatistics 2008 9(3):513-522; doi:10.1093/biostatistics/kxm052
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© 2008 The Authors
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Statistical models for quantifying diagnostic accuracy with multiple lesions per patient

Aeilko H. Zwinderman*, Afina S. Glas and Patrick M. Bossuyt

Department of Clinical Epidemiology and Biostatistics, J2-203, Amsterdam Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, The Netherlands
a.h.zwinderman{at}amc.uva.nl

Jasper Florie, Shandra Bipat and Jaap Stoker

Department of Radiology, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DD Amsterdam, The Netherlands

* To whom correspondence should be addressed.

We propose random-effects models to summarize and quantify the accuracy of the diagnosis of multiple lesions on a single image without assuming independence between lesions. The number of false-positive lesions was assumed to be distributed as a Poisson mixture, and the proportion of true-positive lesions was assumed to be distributed as a binomial mixture. We considered univariate and bivariate, both parametric and nonparametric mixture models. We applied our tools to simulated data and data of a study assessing diagnostic accuracy of virtual colonography with computed tomography in 200 patients suspected of having one or more polyps.

Keywords: Beta-binomial model; Multiple lesions; Nonparametric mixture models; Poisson–gamma model

Received January 31, 2007; revised June 20, 2007; revised October 11, 2007; accepted for publication November 20, 2007.


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