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Abstract Details

Activity Number: 334
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract #322767 View Presentation
Title: A prediction model for understanding statistical replication
Author(s): Andrew Neath*
Companies: SIU Edwardsville
Keywords: hypothesis testing ; Bayesian inference ; statistical evidence ; reproducible research ; scientific method
Abstract:

There is growing concern over the number of scientific findings that fail when replication is attempted. Traditional statistical inference is designed as a look back to how data originates. Perhaps we also need to look ahead in anticipation of what data we will see next. Through the use of a Bayesian prediction model, this paper seeks to determine what can reasonably be expected to occur in a replication trial.


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