editors

Brian Dennis: Journal Editors Be Warned:  Statistics Won’t Be Contained (Guest Post)

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Brian Dennis

Professor Emeritus
Dept Fish and Wildlife Sciences,
Dept Mathematics and Statistical Science
University of Idaho

 

Journal Editors Be Warned:  Statistics Won’t Be Contained

I heartily second Professor Mayo’s call, in a recent issue of Conservation Biology, for science journals to tread lightly on prescribing statistical methods (Mayo 2021).  Such prescriptions are not likely to be constructive;  the issues involved are too vast.

The science of ecology has long relied on innovative statistical thinking.  Fisher himself, inventor of P values and a considerable portion of other statistical methods used by generations of ecologists, helped ecologists quantify patterns of biodiversity (Fisher et al. 1943) and understand how genetics and evolution were connected (Fisher 1930).  G. E. Hutchinson, the “founder of modern ecology” (and my professional grandfather), early on helped build the tradition of heavy consumption of mathematics and statistics in ecological research (Slack 2010). Continue reading

Categories: ecology, editors, Likelihood Principle, Royall | Tags: | 2 Comments

Kent Staley: Commentary on “The statistics wars and intellectual conflicts of interest” (Guest Post)

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Kent Staley

Professor
Department of Philosophy
Saint Louis University

 

Commentary on “The statistics wars and intellectual conflicts of interest” (Mayo editorial)

In her recent Editorial for Conservation Biology, Deborah Mayo argues that journal editors “should avoid taking sides” regarding “heated disagreements about statistical significance tests.” Particularly, they should not impose bans suggested by combatants in the “statistics wars” on statistical methods advocated by the opposing side, such as Wasserstein et al.’s (2019) proposed ban on the declaration of statistical significance and use of p value thresholds. Were journal editors to adopt such proposals, Mayo argues, they would be acting under a conflict of interest (COI) of a special kind: an “intellectual” conflict of interest.

Conflicts of interest are worrisome because of the potential for bias. Researchers will no doubt be all too familiar with the institutional/bureaucratic requirement of declaring financial interests. Whether such disclosures provide substantive protections against bias or simply satisfy a “CYA” requirement of administrators, the rationale is that assessment of research outcomes can incorporate information relevant to the question of whether the investigators have arrived at a conclusion that overstates (or even fabricates) the support for a claim, when the acceptance of that claim would financially benefit them. This in turn ought to reduce the temptation of investigators to engage in such inflation or fabrication of support. The idea obviously applies quite naturally to editorial decisions as well as research conclusions. Continue reading

Categories: conflicts of interest, editors, intellectual COI, significance tests, statistical tests | 5 Comments

E. Ionides & Ya’acov Ritov (Guest Post) on Mayo’s editorial, “The Statatistics Wars and Intellectual Conflicts of Interest”

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Edward L. Ionides

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Director of Undergraduate Programs and Professor,
Department of Statistics, University of Michigan

Ya’acov Ritov Professor
Department of Statistics, University of Michigan

 

Thanks for the clear presentation of the issues at stake in your recent Conservation Biology editorial (Mayo 2021). There is a need for such articles elaborating and contextualizing the ASA President’s Task Force statement on statistical significance (Benjamini et al, 2021). The Benjamini et al (2021) statement is sensible advice that avoids directly addressing the current debate. For better or worse, it has no references, and just speaks what looks to us like plain sense. However, it avoids addressing why there is a debate in the first place, and what are the justifications and misconceptions that drive different positions. Consequently, it may be ineffective at communicating to those swing voters who have sympathies with some of the insinuations in the Wasserstein & Lazar (2016) statement. We say “insinuations” here since we consider that their 2016 statement made an attack on p-values which was forceful, indirect and erroneous. Wasserstein & Lazar (2016) started with a constructive discussion about the uses and abuses of p-values before moving against them. This approach was good rhetoric: “I have come to praise p-values, not to bury them” to invert Shakespeare’s Anthony. Good rhetoric does not always promote good science, but Wasserstein & Lazar (2016) successfully managed to frame and lead the debate, according to Google Scholar. We warned of the potential consequences of that article and its flaws (Ionides et al, 2017) and we refer the reader to our article for more explanation of these issues (it may be found below). Wasserstein, Schirm and Lazar (2019) made their position clearer, and therefore easier to confront. We are grateful to Benjamini et al (2021) and Mayo (2021) for rising to the debate. Rephrasing Churchill in support of their efforts, “Many forms of statistical methods have been tried, and will be tried in this world of sin and woe. No one pretends that the p-value is perfect or all-wise. Indeed (noting that its abuse has much responsibility for the replication crisis) it has been said that the p-value is the worst form of inference except all those other forms that have been tried from time to time”. Continue reading

Categories: ASA Task Force on Significance and Replicability, editors, P-values, significance tests | 2 Comments

B. Haig on questionable editorial directives from Psychological Science (Guest Post)

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Brian Haig, Professor Emeritus
Department of Psychology
University of Canterbury
Christchurch, New Zealand

 

What do editors of psychology journals think about tests of statistical significance? Questionable editorial directives from Psychological Science

Deborah Mayo’s (2021) recent editorial in Conservation Biology addresses the important issue of how journal editors should deal with strong disagreements about tests of statistical significance (ToSS). Her commentary speaks to applied fields, such as conservation science, but it is relevant to basic research, as well as other sciences, such as psychology. In this short guest commentary, I briefly remark on the role played by the prominent journal, Psychological Science (PS), regarding whether or not researchers should employ ToSS. PS is the flagship journal of the Association for Psychological Science, and two of its editors-in-chief have offered explicit, but questionable, advice on this matter. Continue reading

Categories: ASA Task Force on Significance and Replicability, Brian Haig, editors, significance tests | Tags: | 1 Comment

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