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Activity Number:
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504
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Type:
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Contributed
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Date/Time:
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Thursday, August 2, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #308329 |
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Title:
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Empirical Likelihood-Based Inference for the Partial Area Under the ROC Curve
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Author(s):
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Gengsheng Qin*+ and Xiaoping Jin and Xiao-Hua (Andrew) Zhou
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Companies:
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Georgia State University and Centers for Disease Control and Prevention and University of Washington
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Address:
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30 Pryor Street, Atlanta, GA, 30303,
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Keywords:
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ROC ; AUC ; The partial AUC ; Diagnostic test ; Confidence interval
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Abstract:
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Accurate diagnosis of disease is a critical part of health care. New diagnostic and screening tests must be evaluated based on their abilities to discriminate diseased conditions from non-diseased conditions. For a continuous-scale diagnostic test, the most commonly used global summary index of the receiver operating characteristic curve is the area under the curve (AUC). The partial area under the ROC curve (pAUC) is often used when only a region of the ROC curve is of interest. In this paper we propose an empirical likelihood approach for the inference on the partial AUC. We also conduct a simulation study to compare the relative performance of the proposed empirical likelihood based intervals with the existing normal approximation based intervals for the partial AUC. The simulation study indicates that the empirical likelihood based method greatly outperforms the existing method.
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