This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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114
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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Abstract - #307254 |
Title:
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Semiparametric Transformation Models for Multiple Biomarkers in ROC Analysis
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Author(s):
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Eunhee Kim*+ and Donglin Zeng+
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Companies:
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Brown University and The University of North Carolina at Chapel Hill
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Address:
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, , , CB#7420, Gillings School of Global Public Health, Chapel Hill, NC, 27599,
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Keywords:
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Biomarkers ;
ROC analysis ;
Transformation models ;
Nonparametric maximum likelihood estimation ;
Semiparametric efficiency
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Abstract:
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In medical diagnostic research, biomarkers are used as the basis for detecting or predicting disease. In certain situations, a single biomarker is not enough to achieve the desired level of accuracy, and newly discovered biomarkers can provide additional information for a specific disease. Even though numerous methods have been developed for a single biomarker, few statistical methods exist to accommodate multiple biomarkers simultaneously. In this paper, we propose a multivariate binormal ROC model to assess multiple biomarkers. Our model assumes that biomarkers follow multivariate normal distribution after unknown and marker-specific transformations. Random effects are introduced to account for within-subject correlation among biomarkers. Nonparametric maximum likelihood estimation is used for inference and the parameter estimators are shown to be asymptotically normal and efficient.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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