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Abstract:
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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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