Commentary highlights that p-hacking influences Type 1 error rates in literature, suggesting implications for p-value interpretation.
[a slightly adapted version of this blog post is now in press at QJEP: see https://osf.io/ycag9/ for the manuscript and R scripts] In this blog, I'll explain how p-hacking will not lead to a peculiar prevalence of p-values just below .05 (e.g., in the 0.045-0.05 range) in the literature at large, but will instead lead to a difficult to identify increase in the Type 1 error rate across the 0.00-0.05 range.
No takes yet. Share an insight, caveat, or question.
Daniël Lakens (2014) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: