This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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225
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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 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract - #306491 |
Title:
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Optimal Designs for Low-Dose Linear Extrapolation in Carcinogenesis Experiments
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Author(s):
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Melvin Slaighter Munsaka*+
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Companies:
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Takeda Global Research & Development Center, Inc.
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Address:
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675 North Field Drive, Lake Forest, IL, 60045,
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Keywords:
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Optimal design ;
Low dose extraplolation ;
low dose slope
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Abstract:
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This paper investigates the utility of optimal designs in improving inference associated with low-dose linear extrapolation. The investigation is exploratory with the objective of characterizing designs for which the magnitude of the upper confidence limit of the low-dose slope is small. Hence, the question of primary concern is: Can carcinogenesis experiments be designed optimally to make low-dose linear extrapolation less restrictive? A simulation study is used to identify designs that are optimal in the sense that the upper confidence limit of the low-dose slope estimated using a specific model-free extrapolation procedure is minimized. An empirical study is used to identify optimal designs in the sense that the variance of the estimate of the low-dose slope estimated using the one-hit model is minimized.
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