Adaptations on the Use of p -Values for Statistical Inference: An Interpretation of Messages from Recent Public Discussions

Eleni Verykouki and Christos T. Nakas ()
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Eleni Verykouki: Laboratory of Biometry, Department of Agriculture Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly, Fytokou Street, 38446 Volos, Greece
Christos T. Nakas: Laboratory of Biometry, Department of Agriculture Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly, Fytokou Street, 38446 Volos, Greece

Stats, 2023, vol. 6, issue 2, 1-13

Abstract: P -values have played a central role in the advancement of research in virtually all scientific fields; however, there has been significant controversy over their use. “The ASA president’s task force statement on statistical significance and replicability ” has provided a solid basis for resolving the quarrel, but although the significance part is clearly dealt with, the replicability part raises further discussions. Given the clear statement regarding significance, in this article, we consider the validity of p -value use for statistical inference as de facto . We briefly review the bibliography regarding the relevant controversy in recent years and illustrate how already proposed approaches, or slight adaptations thereof, can be readily implemented to address both significance and reproducibility, adding credibility to empirical study findings. The definitions used for the notions of replicability and reproducibility are also clearly described. We argue that any p -value must be reported along with its corresponding s-value followed by ( 1 − α ) % confidence intervals and the rejection replication index.

Keywords: bootstrap distribution; confidence intervals; effect size; hypothesis testing; Shannon’s information transform (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2023
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