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Activity Number: 609
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #315519 View Presentation
Title: A Connection Between Discrepancy Function Estimation and the P-Value
Author(s): Andrew Neath* and Joseph Cavanaugh and Benjamin Riedle
Companies: Southern Illinois University Edwardsville and The University of Iowa and The University of Iowa
Keywords: model selection ; prediction ; decision analysis ; bootstrap
Abstract:

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.


Authors who are presenting talks have a * after their name.

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