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Activity Number:
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402
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 10:30 AM to 12:20 PM
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Sponsor:
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General Methodology
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| Abstract - #302405 |
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Title:
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An Empirical Approach to Sufficient Similarity in Dose-Responsiveness: Utilization of Statistical Distance as a Similarity Measure
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Author(s):
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Scott Marshall*+ and Chris Gennings and LeAnna G. Stork and Linda Teuschler and John Libscomb and Mike DeVito and Kevin M. Crofton
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Companies:
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Virginia Commonwealth University and Virginia Commonwealth University and Monsanto Company and U.S. Environmental Protection Agency and U.S. Environmental Protection Agency and U.S. Environmental Protection Agency and U.S. Environmental Protection Agency
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Address:
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730 East Broad Street, Department of Biostatistics, Richmond, VA, 23298,
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Keywords:
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risk assessment ; chemical mixtures ; non-linear mixed models ; equivalence testing
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Abstract:
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Using statistical equivalence testing logic and mixed model theory an approach has been developed, that extends the work of Stork et al (JABES,2008), to define sufficient similarity in dose-response for chemical mixtures containing the same chemicals with different ratios or a subset of chemicals. The similarity measure is based on statistical distance which is defined as a function of relative potencies of the chemicals. A simulation study was conducted to assess the "power" of the approach. The mixing ratio for exposure to a chemical mixture was assumed to be a random process. The current work estimated how often a resulting candidate mixture was sufficiently similar in dose-responsiveness to the reference mixture. (Partially supported by NIEHS #T32 ES007334 and does not reflect USEPA policy. This research is not associated with Monsanto.)
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