It was 3 months before I decided to write a blogpost in response to Wasserstein, Schirm and Lazar (2019)’s editorial in The American Statistician in which they recommend that the concept of “statistical significance” be abandoned, hereafter, WSL 2019. (I titled it “Don’t Say What You don’t Mean”.) In that June 17, 2019 blogpost, pasted below, I proposed 3 “friendly amendments” to the language of that document. (There are 97 comments on that post!) The problem is that WSL 2019 presents several of the 6 principles from ASA I (the 2016 ASA statement on Statistical Significance) in a far stronger fashion so as to be inconsistent or at least in tension with some of them. I didn’t think they really meant what they said. I discussed these amendments with Ron Wasserstein, Executive Director of the ASA at the time. Had these friendly amendments been carried out, the document would not have caused as much of a problem, and people might focus more on the positive recommendations it includes about scientific integrity. The proposed ban on a key concept of statistics would still be problematic, resulting in the 2019 ASA President’s Task Force, but it would have helped the document. At the time, it was still not known whether WSL 2019 was intended as a continuation of the 2016 ASA policy document [ASA I]. That explains why I first referred to WSL 2019 in this blogpost as ASA II. Once it was revealed that it was not official policy at all (many months later), but only the recommendations of the 3 authors, I placed a “note” after each mention of ASA II. But given it caused sufficient confusion as to result in the then ASA president (Karen Kafadar) appointing an ASA Task Force on Statistical Significance and Replicability in 2019 (see here and here), and later, a disclaimer by the authors, in this reblog I refer to it as WSL 2019. You can search this blog for other posts on the 2019 Task Force: their report is here, and the disclaimer here. Continue reading
2016 ASA Statement on P-values
Invitation to discuss the ASA Task Force on Statistical Significance and Replication
The latest salvo in the statistics wars comes in the form of the publication of The ASA Task Force on Statistical Significance and Replicability, appointed by past ASA president Karen Kafadar in November/December 2019. (In the ‘before times’!) Its members are:
Linda Young, (Co-Chair), Xuming He, (Co-Chair) Yoav Benjamini, Dick De Veaux, Bradley Efron, Scott Evans, Mark Glickman, Barry Graubard, Xiao-Li Meng, Vijay Nair, Nancy Reid, Stephen Stigler, Stephen Vardeman, Chris Wikle, Tommy Wright, Karen Kafadar, Ex-officio. (Kafadar 2020)
The full report of this Task Force is in the The Annals of Applied Statistics, and on my blogpost. It begins:
In 2019 the President of the American Statistical Association (ASA) established a task force to address concerns that a 2019 editorial in The American Statistician (an ASA journal) might be mistakenly interpreted as official ASA policy. (The 2019 editorial recommended eliminating the use of “p < 0.05” and “statistically significant” in statistical analysis.) This document is the statement of the task force… (Benjamini et al. 2021)
Why hasn’t the ASA Board revealed the recommendations of its new task force on statistical significance and replicability?
A little over a year ago, the board of the American Statistical Association (ASA) appointed a new Task Force on Statistical Significance and Replicability (under then president, Karen Kafadar), to provide it with recommendations. [Its members are here (i).] You might remember my blogpost at the time, “Les Stats C’est Moi”. The Task Force worked quickly, despite the pandemic, giving its recommendations to the ASA Board early, in time for the Joint Statistical Meetings at the end of July 2020. But the ASA hasn’t revealed the Task Force’s recommendations, and I just learned yesterday that it has no plans to do so*. A panel session I was in at the JSM, (P-values and ‘Statistical Significance’: Deconstructing the Arguments), grew out of this episode, and papers from the proceedings are now out. The introduction to my contribution gives you the background to my question, while revealing one of the recommendations (I only know of 2). Continue reading





