Abandon Statistical Significance
Northwestern University · University of Illinois Chicago · +3 more institutions
Abstract
We discuss problems the null hypothesis significance testing (NHST) paradigm poses for replication and more broadly in the biomedical and social sciences as well as how these problems remain unresolved by proposals involving modified p-value thresholds, confidence intervals, and Bayes factors. We then discuss our own proposal, which is to abandon statistical significance. We recommend dropping the NHST paradigm—and the p-value thresholds intrinsic to it—as the default statistical paradigm for research, publication, and discovery in the biomedical and social sciences. Specifically, we propose that the p-value be demoted from its threshold screening role and instead, treated continuously, be considered along…
Citation impact
- FWCI
- 74.20
- Percentile
- 100%
- References
- 62
Authors
5- BBBlakeley B. McShaneCorresponding
Northwestern University
- DGDavid Gal
University of Illinois Chicago
- AGAndrew Gelman
Columbia University
- CRChristian Robert
Centre de Recherche en Mathématiques de la Décision, Université Paris Dauphine-PSL
- JLJennifer L. Tackett
Northwestern University
Topics & keywords
- Statistical hypothesis testing
- Novelty
- Null hypothesis
- Replication (statistics)
- Bayes' theorem
- Statistical model
- Process (computing)
- Frequentist probability