Second-generation p-values: Improved rigor, reproducibility, & transparency in statistical analyses

Jeffrey D Blume, Lucy D’Agostino McGowan, William D Dupont and Robert A Greevy

PLOS ONE, 2018, vol. 13, issue 3, 1-17

Abstract: Verifying that a statistically significant result is scientifically meaningful is not only good scientific practice, it is a natural way to control the Type I error rate. Here we introduce a novel extension of the p-value—a second-generation p-value (pδ)–that formally accounts for scientific relevance and leverages this natural Type I Error control. The approach relies on a pre-specified interval null hypothesis that represents the collection of effect sizes that are scientifically uninteresting or are practically null. The second-generation p-value is the proportion of data-supported hypotheses that are also null hypotheses. As such, second-generation p-values indicate when the data are compatible with null hypotheses (pδ = 1), or with alternative hypotheses (pδ = 0), or when the data are inconclusive (0

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0188299

DOI: 10.1371/journal.pone.0188299

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