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Abstract Details
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Activity Number:
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253
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #304830 |
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Title:
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Investigating the General Guidelines for Modeling Extra-Dispersed Proportion Data Based on Some Completing Proportion Models
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Author(s):
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Krishna Saha*+
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Companies:
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Central Connecticut State University
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Address:
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1615 Stanley Street, New Britain, CT, 06050, United States
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Keywords:
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Beta-binomial ;
correlated beta-binomial ;
correlated binomial ;
double binomial ;
over-dispersion ;
toxicological data
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Abstract:
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Proportion data occurring in many applied fields exhibit extra-variation predicted by a simple binomial model. For modeling extra-dispersed proportions, many authors have introduced several alternative extra-dispersed proportion models. With real-life data, a practical problem is deciding how to select one out of a wide variety of candidate models. In this paper, we aim to solve this problem in terms of real-life data occurring in a toxicological study. We discuss the model selection issues using a variety of standard model selection approaches. Moreover, a parametric bootstrap approach of model evaluation using a Mahalanobis squared distance proposed by Allcroft and Glasbey ({\it Statistical Modelling}, 2003) is applied.
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Authors who are presenting talks have a * after their name.
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