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Activity Number:
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104
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #308339 |
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Title:
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Modeling Longitudinal Biomarker Data with Multiple Assays That Have Different Known Detection Limits
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Author(s):
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Paul Albert*+
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Companies:
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National Cancer Institute
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Address:
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6130 Executive Blvd Room 8136, Bethesda, MD, 20906,
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Keywords:
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Abstract:
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Assays to measure biomarkers are commonly subject to large amounts of measurement error and known detection limits. We propose a joint modeling approach for analyzing repeated measures of multiple assays when these assays are subject to measurement error and different known lower detection limits. A commonly used approach is to perform an initial assay with a larger lower detection limit on all repeated samples, followed by only performing a second more expensive assay when the initial assay value is below its lower detection limit. We show how simply replacing the initial assay measurement with the second assay measurement may be a biased approach and investigate the performance of the joint model in this situation. We evaluate different designs and illustrate the methodology with a study examining the use of a vaccine in treating macaques with simian immunodeficiency virus (SIV).
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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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