Abstract Details
Activity Number:
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609
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Type:
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Contributed
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Date/Time:
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Wednesday, August 12, 2015 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract #315519
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View Presentation
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Title:
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A Connection Between Discrepancy Function Estimation and the P-Value
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Author(s):
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Andrew Neath* and Joseph Cavanaugh and Benjamin Riedle
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Companies:
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Southern Illinois University Edwardsville and The University of Iowa and The University of Iowa
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Keywords:
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model selection ;
prediction ;
decision analysis ;
bootstrap
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Abstract:
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Consider the common statistical problem of using data to decide between a null model and a more general alternative. Within the significance testing framework, one will decide in favor of the alternative (reject the null hypothesis) only when the p-value is sufficiently small. Within the discrepancy function / model selection framework, the decision is based on which model is deemed to provide the most accurate depiction of the underlying data generating mechanism. In this talk, we establish a connection between the frameworks. We will show how the probability of selecting the null model under a discrepancy function framework can be estimated by the p-value. Furthermore, we will discuss the implications of imposing significance testing principles on a discrepancy function based model selection problem.
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Authors who are presenting talks have a * after their name.
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