For the last three years, unlike the previous 10 years that I’ve been blogging, it was not feasible to actually revisit that spot in the road, looking to get into a strange-looking taxi, to head to “Midnight With Birnbaum”. But this year I will, and I’m about to leave at 10pm. (The pic on the left is the only blurry image I have of the club I’m taken to.) My book Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (CUP, 2018) doesn’t include the argument from my article in Statistical Science (“On the Birnbaum Argument for the Strong Likelihood Principle”), but you can read it at that link along with commentaries by A. P. David, Michael Evans, Martin and Liu, D. A. S. Fraser, Jan Hannig, and Jan Bjornstad. David Cox, who very sadly did in January 2022, is the one who encouraged me to write and publish it. (The first David R. Cox Foundations of Statistics Prize will be awarded at the JSM 2023.) The (Strong) Likelihood Principle (LP or SLP) remains at the heart of many of the criticisms of Neyman-Pearson (N-P) statistics and of error statistics in general. Continue reading
Likelihood Principle
Midnight With Birnbaum: Happy New Year 2023!
“A [very informal] Conversation Between Sir David Cox & D.G. Mayo”
In June 2011, Sir David Cox agreed to a very informal ‘interview’ on the topics of the 2010 workshop that I co-ran at the London School of Economics (CPNSS), Statistical Science and Philosophy of Science, where he was a speaker. Soon after I began taping, Cox stopped me in order to show me how to do a proper interview. He proceeded to ask me questions, beginning with:
COX: Deborah, in some fields foundations do not seem very important, but we both think foundations of statistical inference are important; why do you think that is?
MAYO: I think because they ask about fundamental questions of evidence, inference, and probability. I don’t think that foundations of different fields are all alike; because in statistics we’re so intimately connected to the scientific interest in learning about the world, we invariably cross into philosophical questions about empirical knowledge and inductive inference.
Brian Dennis: Journal Editors Be Warned: Statistics Won’t Be Contained (Guest Post)
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
Next Phil Stat Forum: January 7: D. Mayo: Putting the Brakes on the Breakthrough (or “How I used simple logic to uncover a flaw in …..statistical foundations”)
The fourth meeting of our New Phil Stat Forum*:
The Statistics Wars
and Their Casualties
January 7, 16:00 – 17:30 (London time)
11 am-12:30 pm (New York, ET)**
**note time modification and date change
Putting the Brakes on the Breakthrough,
or “How I used simple logic to uncover a flaw in a controversial 60-year old ‘theorem’ in statistical foundations”
Deborah G. Mayo

.
Next Phil Stat Forum: January 7: D. Mayo: Putting the Brakes on the Breakthrough (or “How I used simple logic to uncover a flaw in …..statistical foundations”)
The fourth meeting of our New Phil Stat Forum*:
The Statistics Wars
and Their Casualties
January 7, 16:00 – 17:30 (London time)
11 am-12:30 pm (New York, ET)**
**note time modification and date change
Putting the Brakes on the Breakthrough,
or “How I used simple logic to uncover a flaw in a controversial 60-year old ‘theorem’ in statistical foundations”
Deborah G. Mayo

.
HOW TO JOIN US: SEE THIS LINK
ABSTRACT: An essential component of inference based on familiar frequentist (error statistical) notions p-values, statistical significance and confidence levels, is the relevant sampling distribution (hence the term sampling theory). This results in violations of a principle known as the strong likelihood principle (SLP), or just the likelihood principle (LP), which says, in effect, that outcomes other than those observed are irrelevant for inferences within a statistical model. Now Allan Birnbaum was a frequentist (error statistician), but he found himself in a predicament: He seemed to have shown that the LP follows from uncontroversial frequentist principles! Bayesians, such as Savage, heralded his result as a “breakthrough in statistics”! But there’s a flaw in the “proof”, and that’s what I aim to show in my presentation by means of 3 simple examples:
- Example 1: Trying and Trying Again
- Example 2: Two instruments with different precisions
(you shouldn’t get credit/blame for something you didn’t do) - The Breakthrough: Don’t Birnbaumize that data my friend
As in the last 9 years, I will post an imaginary dialogue with Allan Birnbaum at the stroke of midnight, New Year’s Eve, and this will be relevant for the talk.
The Phil Stat Forum schedule is at the Phil-Stat-Wars.com blog