Abstract Details
Activity Number:
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172
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 5, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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Abstract - #308082 |
Title:
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Facilitated Prior Elicitation with the Wolfram CDF
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Author(s):
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David Kahle*+ and James D. Stamey and Karen Lynn Price and Fanni Natanegara and Baoguang Han
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Companies:
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Baylor University and Baylor University and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company
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Keywords:
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Bayesian statistics ;
prior elicitation ;
interactive graphics ;
Wolfram CDF ;
Bayesian computation
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Abstract:
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One of the key advantages of the Bayesian paradigm is the ability to incorporate past experiences and expert opinion into statistical analyses. However, the principled, precise distillation of expert opinion into a probability distribution, a task known as prior elicitation, is challenging and involves considerations from psychology, computational science, software engineering, and other related fields. Moreover, for elicitation to be practical, applied statisticians need good computer tools to enable its use - to perform complex calculations and provide feedback. Such computer programs are called facilitators. Using the prior elicitation of a population proportion as a canonical example, in this article we contend that Wolfram Research Inc.'s novel Mathematica/CDF Player/CDF suite of technologies provides a new state-of-the-art platform for the development and dissemination of free facilitators. To illustrate its capabilities, we present a novel free facilitator that enables, in a real-time interactive environment, the computations and diagnostics required of an elicitation method known as the mode/percentile (MP) method.
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Authors who are presenting talks have a * after their name.
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