Preprint of: "Redefine or Justify? Comments on the alpha debate"
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CC-BY-4.0
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This paper examines the ongoing debate surrounding alpha in statistical testing, proposing a redefinition or justification for its current usage.
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Abstract
Benjamin et al. (2017) proposed improving the reproducibility of findings in psychological research by lowering the alpha level of our conventional Null Hypothesis Significance Tests from .05 to .005, because findings with p-values close to .05 represent insufficient empirical evidence. They argued that findings with a p-value between 0.005 and 0.05 should still be published, but not called “significant” anymore.This proposal was criticized and rejected in a response by Lakens et al. (2018), who argued that instead of lowering the traditional alpha threshold to .005, we should stop using the term “statistically significant”, and require researchers to determine and justify their alpha levels before they collect data.In this contribution, I argue that the arguments presented by Lakens et al. against the proposal by Benjamin et al (2017) are not convincing. Thus, given that it is highly unlikely that our field will abandon the NHST paradigm any time soon, lowering our alpha level to .005 is at this moment the best way to combat the replication crisis in psychology.
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- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-4.0