D. Lakens

Guest Post (part 2 of 2): Daniël Lakens: “How were we supposed to move beyond  p < .05, and why didn’t we?”

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Professor Daniël Lakens
Human Technology Interaction
Eindhoven University of Technology

[Some earlier posts by D. Lakens on this topic are at the end of this post]*

This continues Part 1:

4: Most do not offer any alternative at all

At this point, it might be worthwhile to point out that most of the contributions to the special issue do not discuss alternative approaches to p < .05 at all. They discuss general problems with low quality research (Kmetz, 2019), the importance of improving quality control (D. W. Hubbard & Carriquiry, 2019), results blind reviewing (Locascio, 2019), or the role of subjective judgment (Brownstein et al., 2019). There are historical perspectives on how we got to this point (Kennedy-Shaffer, 2019), ideas about how science should work instead, many stressing the importance of replication studies (R. Hubbard et al., 2019; Tong, 2019). Note that Trafimow both recommends replication as an alternative (Trafimow, 2019), but also co-authors a paper stating we should not expect findings to replicate (Amrhein et al., 2019), thereby directly contradicting himself within the same special issue. Others propose not simply giving up on p-values, but on generalizable knowledge (Amrhein et al., 2019). The suggestion is to only report descriptive statistics. Continue reading

Categories: abandon statistical significance, D. Lakens, Wasserstein et al 2019 | 13 Comments

Guest Post: “Daniël Lakens: How were we supposed to move beyond  p < .05, and why didn’t we? “(part 1 of 2):

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Professor Daniël Lakens
Human Technology Interaction
Eindhoven University of Technology

*[Some earlier posts by D. Lakens on this topic are listed at the end of part 2, forthcoming this week]

How were we supposed to move beyond  p < .05, and why didn’t we?

It has been 5 years since the special issue “Moving to a world beyond p < .05” came out (Wasserstein et al., 2019). I might be the only person in the world who has read all 43 contributions to this special issue. [In part 1] I will provide a summary of what the articles proposed we should do instead of p < .05, and [in part 2] offer some reflections on why they did not lead to any noticeable change. Continue reading

Categories: abandon statistical significance, D. Lakens, Wasserstein et al. (2019) | 23 Comments

D. Lakens (Guest Post): Averting journal editors from making fools of themselves

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Daniël Lakens

Associate Professor
Human Technology Interaction
Eindhoven University of Technology

Averting journal editors from making fools of themselves

In a recent editorial, Mayo (2021) warns journal editors to avoid calls for authors guidelines to reflect a particular statistical philosophy, and not to go beyond merely enforcing the proper use of significance tests. That such a warning is needed at all should embarrass anyone working in statistics. And yet, a mere three weeks after Mayo’s editorial was published, the need for such warnings was reinforced when a co-editorial by journal editors from the International Society of Physiotherapy (Elkins et al., 2021) titled “Statistical inference through estimation: recommendations from the International Society of Physiotherapy Journal Editors” stated: “[This editorial] also advises researchers that some physiotherapy journals that are members of the International Society of Physiotherapy Journal Editors (ISPJE) will be expecting manuscripts to use estimation methods instead of null hypothesis statistical tests.” Continue reading

Categories: D. Lakens, significance tests | 4 Comments

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