März 2022 Archiv

An awareness of the history of p-values might help deflate their swollen stature and encourage more judicious use. We were surprised to learn, in the course of writing this article, that the p < 0.05 cutoff was established as a competitive response to a disagreement over book royalties between two foundational statisticians. In the early 1920s, Kendall Pearson, whose income depended on the sale of extensive statistical tables, was unwilling to allow Ronald A. Fisher to use them in his new book. To work around this barrier, Fisher created a method of inference based on only two values: p-values of 0.05 and 0.01 (Hurlbert and Lombardi, 2009). Fisher himself later admitted that Pearson's more continuous method of inference was better than his binary approach: “no scientific worker has a fixed level of significance at which from year to year, and in all circumstances, he rejects [null] hypotheses; he rather gives his mind to each particular case in the light of his evidence and ideas” (Hurlbert and Lombardi, 2009: 316). A fair interpretation of this history is that we use p-values at least in part because a statistician from the 1920s was afraid that sharing his work would undermine his income (Hurlbert and Lombardi, 2009). Following Fischer, we recommend that authors report p-values and refrain from emphasizing thresholds. This will allow us to more easily interpret evidence on a continuum and in the context of previous findings.

Goldfarb & King (2015): Scientific apophenia in strategic management research: Significance tests & mistaken inference https://doi.org/10.1002/smj.2459