Someone sent me an email the other day telling me that a disclaimer had been added to the editorial written by the ASA Executive Director and 2 co-authors (Wasserstein et al., 2019) (“Moving to a world beyond ‘p < 0.05′”). It reads:
The editorial was written by the three editors acting as individuals and reflects their scientific views not an an endorsed position of the American Statistical Association.
The person who informed me, who does not wish to be named, also told me there had been a symposium on June 3 to discuss these issues: Scientific Reproducibility and Statistical Significance Symposium. Are the two events related? Perhaps the disclaimer was announced at that forum? I really don’t know. The description of the Symposium reads:
All researchers agree that the scientific method of experimentation and replication must be preserved. To date, null hypothesis significance testing is the best way to assure that random error is accounted for in the analysis of scientific experiments and surveys. Although the statistics community has been talking the misuse of significance testing, and some inroads have been made into statistics education, the conversation among statisticians has not reached the scientific community on a large scale.
The aim of the symposium on scientific inquiry and statistical significance is four-fold:
1. To disseminate the stance of the American Statistical Association on the appropriate use of results from null hypothesis significance testing for analysis of studies from social science, science, engineering, and humanities.
[June 20 update: The Symposium organizer shifts on this first goal in her description.
See my comment]
2. To offer alternatives to such testing
3. To discuss changes to publication policies that would benefit both individual scientists and science writ large.
4. To discuss methods of educating current and future scientists in appropriate methods for gathering and analyzing data.
The first question that comes to my mind is this: if “all researchers agree that …null hypothesis significance testing is the best way to assure that random error is accounted for in the analysis of scientific experiments and surveys” then why is one of the 4 aims of the symposium: to offer alternatives to such [statistical significance] testing”? It seems peculiar to say that all researchers agree a method is best for accomplishing a central, if limited, task for which scientists look to statistics, so let’s find alternatives to replace it. [1, 1a, 1b]
And what about the first goal “To disseminate the stance of the American Statistical Association on the appropriate use of results from null hypothesis significance testing…”? An ASA Task Force just recently put forward a statement on statistical significance and replicability (Benjamini et al., 2021), so it would make sense for the dissemination of the ASA stance to be an affirmation of the. 2021 Task Force Statement on Statistical Significance and Replicability. But that would be a policy shift by the ASA, if I understand it correctly, and the symposium program shows no sign that is what is meant. Aside from Kafadar, ex officio, no members of this Task Force are on the program. (Don’t confuse the 2021 ASA Task Force statement with the 2016 ASA Statement on p-values–which is an ASA policy statement). This is all very confusing. For a bit of the background, I’ve pasted a few relevant links from this blog below (searching this blog will find others).
I look forward to listening to the recording of the meeting when it is available.
So is the disclaimer 3+ years after Wasserstein et al., 2019 too little too late? Granted, had such a disclaimer been added to the editorial in December 2019, there would not have been a need for Karen Kafadar (then ASA President) to appoint the task force on statistical significance and replicability in 2019. 
Concerned that WSL 2019 might be taken as a continuation of the 2016 ASA Statement, in 2019 the Board of the ASA appointed a President’s Task Force on Statistical Significance and Replicability. It was put in the odd position of needing to “address concerns that [the Executive Director’s editorial, WSL 2019] might be mistakenly interpreted as official ASA policy” (Benjamini et al., 2021). From Mayo and Hand (2022):
But I don’t think it’s possible to neutralize by disclaimer the effect of Wasserstein et al., 2019. [See note 3] Besides, in my view, what is really needed are revisions to some of the claims made within it (and I’m referring just to the first couple of pages, not the discussion of the articles by various others in introducing the special issue). If such revisions were made, people could appreciate some of the many useful suggestions in Wasserstein et al., 2019. Early on, I proposed several simple revisions in private communication with Wasserstein, hoping to improve the document. Some are in the following blogpost:
June 17, 2019: “The 2019 ASA Guide to P-values and Statistical Significance: Don’t Say What You Don’t Mean” (Some Recommendations)(ii)
I doubt the authors (Wasserstein, Schirm and Lazar) really and truly mean many of the claims alleged to warrant “abandoning” statistical significance (in fact, some are at odds with the 2016 ASA statement on p-values)–which, to repeat, is ASA policy, but is quire controversial nevertheless. Or, if they do, much more in the way of warranting them is needed (see Mayo and Hand 2022).
Please share your constructive thoughts on this in the comments.
 Anyone who reads this blog knows I don’t like the “null hypothesis significance test” label, as it wrongly assumes a very artificial context with a point null with no alternatives. Worse, the label NHST is often used to describe a flawed methodology that commits all the central fallacies: construes a p-value as a posterior, takes statistical as substantive, supposes a small p-value means a large effect size, etc.
[1a] Added June 16, 2022. To be clear, I think that both p-values, and the standard N-P (accept/reject) testing methodology call for reformulation and reinterpretation. I have proposed such reformulations based on a severe testing philosophy. Here, error probabilities are used to qualify how well (and poorly) tested claims are. Fallacies of statistical significance and insignificance are avoided. However, the “alternatives” that are put forward to replace statistical significance assume notions of evidence and inference that are often at odds with the error statistical goals of significance tests.
[1b] Added June 20. Aside from the organizer changing the description of goal #1 (in the ASA Connect discussion) we also learn that the 2016 ASA Statement on P-values was not a statement on null hypothesis significance testing. Hmm. See my comment.
 Kafadar provided the ASA Board with over 40 examples showing the mistaken reference to Wasserstein et al., 2019 as ASA policy. She was part of a JSM panel I organized on the general topic in 2020. My slides are in this post. Kafadar’s slides are here. Stan Young, Yaacov Ritov, and Larry Wasserman were also part of the session.
 As ASA Executive Director, Wasserstein is an official ASA spokesperson. So announcing his view (on a matter hotly disputed by ASA members) has a strong impact on others even if he demurs: “I’m just wearing my hat as an individual”. The only solution, I argue, is for officials not to take sides on this type of issue–something I qualify in my 2021/22 Editorial in Conservation Biology.
Some blogposts of relevance for background are:
March 25, 2019: “Diary for Statistical War Correspondents on the Latest Ban on Speech.”
July 19, 2019: “The NEJM Issues New Guidelines on Statistical Reporting: Is the ASA P-Value Project Backfiring? (i)”
September 19, 2019: “(Excerpts from) ‘P-Value Thresholds: Forfeit at Your Peril’ (free access).” The article by Hardwicke and Ioannidis (2019), and the editorials by Gelman and by me are linked on this post.
November 4, 2019: “On some Self-defeating aspects of the ASA’s 2019 recommendations of statistical significance tests”
November 14, 2019: “The ASA’s P-value Project: Why it’s Doing More Harm than Good (cont from 11/4/19)”
November 30, 2019: “P-Value Statements and Their Unintended(?) Consequences: The June 2019 ASA President’s Corner (b)”
December 13, 2019: “’Les stats, c’est moi’: We take that step here! (Adopt our fav word or phil stat!)(iii)”
August 4, 2020: “August 6: JSM 2020 Panel on P-values & ‘Statistical significance’”
December 13, 2020: “The Statistics Debate (NISS) in Transcript Form”
January 9, 2021: “Why hasn’t the ASA Board revealed the recommendations of its new task force on statistical significance and replicability?”
June 20, 2021: “At Long Last! The ASA President’s Task Force Statement on Statistical Significance and Replicability”
June 28, 2021: “Statisticians Rise Up To Defend (error statistical) Hypothesis Testing”
July 30, 2021: “Invitation to discuss the ASA Task Force on Statistical Significance and Replication”
February 24, 2022: “January 11 Forum: “Statistical Significance Test Anxiety”: Benjamini, Mayo, Hand”.
May 15, 2022: “3 commentaries on my editorial are being published in Conservation Biology“
[This post includes links to all of the 12 commentaries on my editorial from Jan 5.]