Abstract #301394


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JSM 2002 Abstract #301394
Activity Number: 22
Type: Contributed
Date/Time: Sunday, August 11, 2002 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section*
Abstract - #301394
Title: Receiver Operating Characteristic Curves with Clustered Data
Author(s): Mithat Gonen*+ and Colin Begg
Affiliation(s): Memorial Sloan-Kettering Cancer Center and Memorial Sloan-Kettering Cancer Center
Address: 1275 York Ave Box 44, New York, New York, 10021,
Keywords: diagnostic test ; AUC ; ROC
Abstract:

Receiver operating characteristic curves (ROC) are accepted as the standard way to evaluate the accuracy of diagnostic tests. With the advent of new modalities, such as positron emission tomography (PET), it is becoming increasingly common to perform whole-body scans which generate several data points per patient. This leads to a clustered data structure, which needs to be taken into account when constructing the ROC curves, computing the area under the curve (AUC,) and the variance of the AUC. Here we propose a hierarchical model that can be used to generate site-specific ROC curves as well as an overall ROC curve. We illustrate our method using standardized uptake values from a study of PET scans in detecting recurrent head and neck cancer.


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