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Abstract Details

Activity Number: 424
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 3:05 PM to 3:50 PM
Sponsor: Section on Statistical Education
Abstract #325118
Title: A prediction model for understanding statistical replication
Author(s): Andrew Neath*
Companies: SIU Edwardsville
Keywords: hypothesis testing ; effect size
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.


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

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