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Toward Replicability With Confidence Intervals for the Exceedance Probability

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  • Brian D. Segal

Abstract

Several scientific fields including psychology are undergoing a replication crisis. There are many reasons for this problem, one of which is a misuse of p-values. There are several alternatives to p-values, and in this article we describe a complement that is geared toward replication. In particular, we focus on confidence intervals for the probability that a parameter estimate will exceed a specified value in an exact replication study. These intervals convey uncertainty in a way that p-values and standard confidence intervals do not, and can help researchers to draw sounder scientific conclusions. After briefly reviewing background on p-values and a few alternatives, we describe our approach and provide examples with simulated and real data. For linear models, we also describe how confidence intervals for the exceedance probability are related to p-values and confidence intervals for parameters.

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  • Brian D. Segal, 2021. "Toward Replicability With Confidence Intervals for the Exceedance Probability," The American Statistician, Taylor & Francis Journals, vol. 75(2), pages 128-138, May.
    • Handle: RePEc:taf:amstat:v:75:y:2021:i:2:p:128-138
    DOI: 10.1080/00031305.2019.1678521
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