Zwinderman, Aeilko H.; Glas, Afina S.; Bossuyt, Patrick M.; Florie, Jasper; Bipat, Shandra; Stoker, Jaap Statistical models for quantifying diagnostic accuracy with multiple lesions per patient. (English) Zbl 1143.62089 Biostatistics 9, No. 3, 513-522 (2008). Summary: 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. MSC: 62P10 Applications of statistics to biology and medical sciences; meta analysis 92C50 Medical applications (general) 62N02 Estimation in survival analysis and censored data Keywords:beta-binomial model; multiple lesions; nonparametric mixture models; Poisson-gamma model PDFBibTeX XMLCite \textit{A. H. Zwinderman} et al., Biostatistics 9, No. 3, 513--522 (2008; Zbl 1143.62089) Full Text: DOI