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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.
Here are all the slides along with the video from the 11 January Phil Stat Forum with speakers: Deborah G. Mayo, Yoav Benjamini and moderator/discussant David Hand.
D. Mayo Y. Benjamini. D. Hand
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Nathan Schachtman, Esq., J.D.
Legal Counsel for Scientific Challenges
Of Significance, Error, Confidence, and Confusion – In the Law and In Statistical Practice
The metaphor of law as an “empty vessel” is frequently invoked to describe the law generally, as well as pejoratively to describe lawyers. The metaphor rings true at least in describing how the factual content of legal judgments comes from outside the law. In many varieties of litigation, not only the facts and data, but the scientific and statistical inferences must be added to the “empty vessel” to obtain a correct and meaningful outcome. Continue reading
The seventh meeting of our Phil Stat Forum*:
The Statistics Wars
and Their Casualties
25 March, 2021
TIME: 15:00-16:45 (London); 11:00-12:45 (New York, NOTE TIME CHANGE TO MATCH UK TIME**)
For information about the Phil Stat Wars forum and how to join, click on this link.
“How should applied science journal editors deal with statistical controversies?“
Mark Burgman Continue reading
The seventh meeting of our Phil Stat Forum*:
The Statistics Wars
and Their Casualties
25 March, 2021
TIME: 15:00-16:45 (London); 11:00-12:45 (New York, NOTE TIME CHANGE)
For information about the Phil Stat Wars forum and how to join, click on this link.
“How should applied science journal editors deal with statistical controversies?“
Mark Burgman Continue reading
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Live Exhibit: So what happens if you replace “p-values” with “Bayes Factors” in the 6 principles from the 2016 American Statistical Association (ASA) Statement on P-values? (Remove “or statistical significance” in question 5.)
Does the one positive assertion hold? Are the 5 “don’ts” true? Continue reading
July 30 PRACTICE VIDEO for JSM talk (All materials for Practice JSM session here)
JSM 2020 Panel Flyer (PDF)
JSM online program w/panel abstract & information):
Mayo fights fire w/ fire
I. Doubt is Their Product is the title of a (2008) book by David Michaels, Assistant Secretary for OSHA from 2009-2017. I first mentioned it on this blog back in 2011 (“Will the Real Junk Science Please Stand Up?) The expression is from a statement by a cigarette executive (“doubt is our product”), and the book’s thesis is explained in its subtitle: How Industry’s Assault on Science Threatens Your Health. Imagine you have just picked up a book, published in 2020: Bad Statistics is Their Product. Is the author writing about how exaggerating bad statistics may serve in the interest of denying well-established risks? [Interpretation A]. Or perhaps she’s writing on how exaggerating bad statistics serves the interest of denying well-established statistical methods? [Interpretation B]. Both may result in distorting science and even in dismantling public health safeguards–especially if made the basis of evidence policies in agencies. A responsible philosopher of statistics should care. Continue reading
les stats, c’est moi
When it comes to the statistics wars, leaders of rival tribes sometimes sound as if they believed “les stats, c’est moi”. [1]. So, rather than say they would like to supplement some well-known tenets (e.g., “a statistically significant effect may not be substantively important”) with a new rule that advances their particular preferred language or statistical philosophy, they may simply blurt out: “we take that step here!” followed by whatever rule of language or statistical philosophy they happen to prefer (as if they have just added the new rule to the existing, uncontested tenets). Karan Kefadar, in her last official (December) report as President of the American Statistical Association (ASA), expresses her determination to call out this problem at the ASA itself. (She raised it first in her June article, discussed in my last post.) Continue reading
Mayo writing to Kafadar
I never met Karen Kafadar, the 2019 President of the American Statistical Association (ASA), but the other day I wrote to her in response to a call in her extremely interesting June 2019 President’s Corner: “Statistics and Unintended Consequences“:
I only recently came across her call, and I will share my letter below. First, here are some excerpts from her June President’s Corner (her December report is due any day). Continue reading
cure by committee
Everything is impeach and remove these days! Should that hold also for the concept of statistical significance and P-value thresholds? There’s an active campaign that says yes, but I aver it is doing more harm than good. In my last post, I said I would count the ways it is detrimental until I became “too disconsolate to continue”. There I showed why the new movement, launched by Executive Director of the ASA (American Statistical Association), Ronald Wasserstein (in what I dub ASA II(note)), is self-defeating: it instantiates and encourages the human-all-too-human tendency to exploit researcher flexibility, rewards, and openings for bias in research (F, R & B Hypothesis). That was reason #1. Just reviewing it already fills me with such dismay, that I fear I will become too disconsolate to continue before even getting to reason #2. So let me just quickly jot down reasons #2, 3, 4, and 5 (without full arguments) before I expire. Continue reading
Mayo banging head
If you were on a committee to highlight issues surrounding P-values and replication, what’s the first definition you would check? Yes, exactly. Apparently, when it came to the recently released National Academies of Science “Consensus Study” Reproducibility and Replicability in Science 2019, no one did. Continue reading
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The October 2019 issue of the European Journal of Clinical Investigations came out today. It includes the PERSPECTIVE article by Tom Hardwicke and John Ioannidis, an invited editorial by Gelman and one by me:
Petitions in scientific argumentation: Dissecting the request to retire statistical significance, by Tom Hardwicke and John Ioannidis
When we make recommendations for scientific practice, we are (at best) acting as social scientists, by Andrew Gelman
P-value thresholds: Forfeit at your peril, by Deborah Mayo
I blogged excerpts from my preprint, and some related posts, here.
All agree to the disagreement on the statistical and metastatistical issues: Continue reading
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A key recognition among those who write on the statistical crisis in science is that the pressure to publish attention-getting articles can incentivize researchers to produce eye-catching but inadequately scrutinized claims. We may see much the same sensationalism in broadcasting metastatistical research, especially if it takes the form of scapegoating or banning statistical significance. A lot of excitement was generated recently when Ron Wasserstein, Executive Director of the American Statistical Association (ASA), and co-editors A. Schirm and N. Lazar, updated(note) the 2016 ASA Statement on P-Values and Statistical Significance (ASA I). In their 2019 interpretation, ASA I “stopped just short of recommending that declarations of ‘statistical significance’ be abandoned,” and in their new statement (ASA II)(note) announced: “We take that step here….’statistically significant’ –don’t say it and don’t use it”. To herald the ASA II(note), and the special issue “Moving to a world beyond ‘p < 0.05’”, the journal Nature requisitioned a commentary from Amrhein, Greenland and McShane “Retire Statistical Significance” (AGM). With over 800 signatories, the commentary received the imposing title “Scientists rise up against significance tests”! Continue reading
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Nathan Schachtman (who was a special invited speaker at our recent Summer Seminar in Phil Stat) put up a post on his law blog the other day (“Palavering About P-values”) on an article by a statistics professor at Stanford, Helena Kraemer. “Palavering” is an interesting word choice of Schachtman’s. Its range of meanings is relevant here [i]; in my title, I intend both, in turn. You can read Schachtman’s full post here, it begins like this:
The American Statistical Association’s most recent confused and confusing communication about statistical significance testing has given rise to great mischief in the world of science and science publishing.[ASA II 2019]note Take for instance last week’s opinion piece about “Is It Time to Ban the P Value?” Please.
Admittedly, their recent statement, which I refer to as ASA II,note has seemed to open the floodgates to some very zany remarks about P-values, their meaning and role in statistical testing. Continuing with Schachtman’s post: Continue reading
The New England Journal of Medicine NEJM announced new guidelines for authors for statistical reporting yesterday*. The ASA describes the change as “in response to the ASA Statement on P-values and Statistical Significance and subsequent The American Statistician special issue on statistical inference” (ASA I and II,(note) in my abbreviation). If so, it seems to have backfired. I don’t know all the differences in the new guidelines, but those explicitly noted appear to me to move in the reverse direction from where the ASA I and II(note) guidelines were heading.
The most notable point is that the NEJM highlights the need for error control, especially for constraining the Type I error probability, and pays a lot of attention to adjusting P-values for multiple testing and post hoc subgroups. ASA I included an important principle (#4) that P-values are altered and may be invalidated by multiple testing, but they do not call for adjustments for multiplicity, nor do I find a discussion of Type I or II error probabilities in the ASA documents. NEJM gives strict requirements for controlling family-wise error rate or false discovery rates (understood as the Benjamini and Hochberg frequentist adjustments). Continue reading
Brian Haig, Professor Emeritus
Department of Psychology
University of Canterbury
Christchurch, New Zealand
The American Statistical Association’s (ASA) recent effort to advise the statistical and scientific communities on how they should think about statistics in research is ambitious in scope. It is concerned with an initial attempt to depict what empirical research might look like in “a world beyond p<0.05” (The American Statistician, 2019, 73, S1,1-401). Quite surprisingly, the main recommendation of the lead editorial article in the Special Issue of The American Statistician devoted to this topic (Wasserstein, Schirm, & Lazar, 2019; hereafter, ASA II(note)) is that “it is time to stop using the term ‘statistically significant’ entirely”. (p.2) ASA II(note) acknowledges the controversial nature of this directive and anticipates that it will be subject to critical examination. Indeed, in a recent post, Deborah Mayo began her evaluation of ASA II(note) by making constructive amendments to three recommendations that appear early in the document (‘Error Statistics Philosophy’, June 17, 2019). These amendments have received numerous endorsements, and I record mine here. In this short commentary, I briefly state a number of general reservations that I have about ASA II(note). Continue reading
Some have asked me why I haven’t blogged on the recent follow-up to the ASA Statement on P-Values and Statistical Significance (Wasserstein and Lazar 2016)–hereafter, ASA I. They’re referring to the editorial by Wasserstein, R., Schirm, A. and Lazar, N. (2019)–hereafter, ASA II(note)–opening a special on-line issue of over 40 contributions responding to the call to describe “a world beyond P < 0.05”.[1] Am I falling down on the job? Not really. All of the issues are thoroughly visited in my Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars, SIST (2018, CUP). I invite interested readers to join me on the statistical cruise therein.[2] As the ASA II(note) authors observe: “At times in this editorial and the papers you’ll hear deep dissonance, the echoes of ‘statistics wars’ still simmering today (Mayo 2018)”. True, and reluctance to reopen old wounds has only allowed them to fester. However, I will admit, that when new attempts at reforms are put forward, a philosopher of science who has written on the statistics wars ought to weigh in on the specific prescriptions/proscriptions, especially when a jumble of fuzzy conceptual issues are interwoven through a cacophony of competing reforms. (My published comment on ASA I, “Don’t Throw Out the Error Control Baby With the Bad Statistics Bathwater” is here.) Continue reading
Neyman
Neyman, confronted with unfortunate news would always say “too bad!” At the end of Jerzy Neyman’s birthday week, I cannot help imagining him saying “too bad!” as regards some twists and turns in the statistics wars. First, too bad Neyman-Pearson (N-P) tests aren’t in the ASA Statement (2016) on P-values: “To keep the statement reasonably simple, we did not address alternative hypotheses, error types, or power”. An especially aggrieved “too bad!” would be earned by the fact that those in love with confidence interval estimators don’t appreciate that Neyman developed them (in 1930) as a method with a precise interrelationship with N-P tests. So if you love CI estimators, then you love N-P tests! Continue reading
When science writers, especially “statistical war correspondents”, contact you to weigh in on some article, they may talk to you until they get something spicy, and then they may or may not include the background context. So a few writers contacted me this past week regarding this article (“Retire Statistical Significance”)–a teaser, I now suppose, to advertise the ASA collection(note) growing out of that conference “A world beyond P ≤ .05” way back in Oct 2017, where I gave a paper*. I jotted down some points, since Richard Harris from NPR needed them immediately, and I had just gotten off a plane when he emailed. He let me follow up with him, which is rare and greatly appreciated. So I streamlined the first set of points, and dropped any points he deemed technical. I sketched the third set for a couple of other journals who contacted me, who may or may not use them. Here’s Harris’ article, which includes a couple of my remarks. Continue reading
Experts convene to explore new philosophy of statistics field
Error Statistics Philosophy 