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190 – Contributed Oral Poster Presentations: Section on Risk Analysis

Decision Analysis, Social Choice Theory, and Model Selection

Sponsor: Section on Risk Analysis
Keywords: model selection, resampling, conceptual predictive statistic

Joseph Cavanaugh

University of Iowa

Andrew Neath

SIU Edwardsville

Adam Weyhaupt

SIU Edwardsville

A discrepancy function provides for an evaluation of a candidate model by quantifying the disparity between the candidate model and the true model which generated the observed data. The best model from a candidate class is the one judged to have minimum discrepancy with the true model. Since data provides only partial information on the underlying true model, we consider taking repeated simulations using some resampling procedure as each representing some possibility for the true model. Each of the candidate models can be judged against each of the simulated versions of the true model. Model evaluation is then achieved by providing an overall judgment on each candidate model. As social choice theory, or voting theory, addresses the problem of turning individual preferences into a group preference, we see that social choice theory can be used in developing a new approach to model evaluation.

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