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Activity Number:
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113
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Type:
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Contributed
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Date/Time:
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Monday, August 7, 2006 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #307445 |
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Title:
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Analysis of Medical Diagnostic Test Data with a Test Ignorance Region
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Author(s):
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Andrzej Kosinski*+
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Companies:
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Duke University
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Address:
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Department of Biostatistics and Bioinformatics, Durham, NC, 27715-7969,
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Keywords:
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medical diagnostic test ; test ignorance region ; missing gold standard ; sensitivity ; specificity
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Abstract:
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When collecting data for a diagnostic test evaluation, one often finds that not all patients undergoing the test have their disease status verified with the gold standard. In this situation, point estimates for sensitivity and specificity of a test are only possible under more or less realistic assumptions about the missing data. The Test Ignorance Region (TIR) (Kosinski and Barnhart 2003) is an assumption free region encompassing all combinations of sensitivity and specificity values compatible with the observed data. We argue that the TIR should be a routine reporting tool for a first step in evaluation of a diagnostic test when the gold standard is partially missing. This way the information included in the actually observed data and "information" induced by assumptions can be clearly separated. More recent extensions to sub-regions will be discussed and real data examples analyzed.
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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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