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

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article

Eleni Verykouki¹  Christos T. Nakas¹ 

[1] Laboratory of Biometry, Department of Agriculture Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly;Laboratory of Entomology and Agricultural Zoology, Department of Agriculture Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly;Institute of Clinical Chemistry, Inselspital, Bern University Hospital, University of Bern

关键词: bootstrap distribution;    confidence intervals;    effect size;    hypothesis testing;    Shannon’s information transform;   

DOI  :  10.3390/stats6020035

学科分类：农艺学与作物科学

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY