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Abstract Details
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Activity Number:
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634
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #301617 |
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Title:
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Nonparametric Analysis of Clustered ROC Curve Data: Optimal Weight Determination
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Author(s):
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Yougui Wu*+
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Companies:
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University of South Florida
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Address:
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13201 Bruce B. Downs Blvd., MDC56, Tampa, FL, 33612, USA
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Keywords:
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Nonparametric estimation ;
ROC ;
Optimal weights ;
Area under ROC
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Abstract:
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In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed.A nonparametric method has been proposed by Nancy A. Obuchowski,Nancy(1997,Biometrics 53,567-578) to estimate the Receiver Operating Characteristic curve area(AUC)for clustered data. However, her estimate gives equal weight to all pairwise rankings within and between cluster regardless of within-patient correlation and the number of affected units in a cluster,which varies among clusters.In this paper, we modify Obuchowski's estimate by allowing different weight for the pairwise rankings within and between cluster. We consider the optimal weights that minimizes the variance of the estimate of the area under the ROC curve with unknown weights.Our results in this paper show that the optimal weights depends on not only thewithin-patient correlation but also the proportion of patients tha
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Authors who are presenting talks have a * after their name.
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