**October 15, Noon – 2 pm ET (Website)**

*Where do ***YOU **stand?

**YOU**stand?

Given the issues surrounding the misuses and abuse of p-values, do you think p-values should be used? Continue reading

**October 15, Noon – 2 pm ET (Website)**

Given the issues surrounding the misuses and abuse of p-values, do you think p-values should be used? Continue reading

Categories: Announcement, J. Berger, P-values, Philosophy of Statistics, reproducibility, statistical significance tests, Statistics
Tags: NISS
9 Comments

**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):

** Today is Allan Birnbaum’s birthday. In honor of his birthday, I’m posting the articles in the Synthese volume that was dedicated to his memory in 1977. The editors describe it as their way of “paying homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics”. I had posted the volume before, but there are several articles that are very worth rereading. I paste a few snippets from the articles by Giere and Birnbaum. If you’re interested in statistical foundations, and are unfamiliar with Birnbaum, here’s a chance to catch up. (Even if you are, you may be unaware of some of these key papers.)** Continue reading

Categories: Birnbaum, Likelihood Principle, Statistics, strong likelihood principle
Tags: Birnbaum
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I will run a graduate Research Seminar at the LSE on Thursdays from May 21-June 18:

(See my new blog for specifics (phil-stat-wars.com).

I am co-running a workshop

from 19-20 June, 2020 at LSE (Center for the Philosophy of Natural and Social Sciences CPNSS), with Roman Frigg. Participants include:

If you have a particular Phil Stat event you’d like me to advertise, please send it to me.

Categories: Announcement, Philosophy of Statistics
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This article came out on Monday on our Summer Seminar in Philosophy of Statistics in Virginia Tech News Daily magazine.

October 28, 2019

*From universities around the world, participants in a summer session gathered to discuss the merits of the philosophy of statistics. Co-director Deborah Mayo, left, hosted an evening for them at her home.*

Categories: Philosophy of Statistics, Summer Seminar in PhilStat
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In marking Egon Pearson’s birthday (Aug. 11), I’ll post some Pearson items this week. They will contain some new reflections on older Pearson posts on this blog. Today, I’m posting “Statistical Concepts in Their Relation to Reality” (Pearson 1955). I’ve linked to it several times over the years, but always find a new gem or two, despite its being so short. E. Pearson rejected some of the familiar tenets that have come to be associated with Neyman and Pearson (N-P) statistical tests, notably the idea that the essential justification for tests resides in a long-run control of rates of erroneous interpretations–what he termed the “behavioral” rationale of tests. In an unpublished letter E. Pearson wrote to Birnbaum (1974), he talks about N-P theory admitting of two interpretations: behavioral and evidential:

“I think you will pick up here and there in my own papers signs of evidentiality, and you can say now that we or I should have stated clearly the difference between the behavioral and evidential interpretations. Certainly we have suffered since in the way the people have concentrated (to an absurd extent often) on behavioral interpretations”.

(Nowadays, it might be said that some people concentrate to an absurd extent on “science-wise error rates” in their view of statistical tests as dichotomous screening devices.) Continue reading

This was published today on the American Philosophical Association blog.

“[C]onfusion about the foundations of the subject is responsible, in my opinion, for much of the misuse of the statistics that one meets in fields of application such as medicine, psychology, sociology, economics, and so forth.” (George Barnard 1985, p. 2)

“Relevant clarifications of the nature and roles of statistical evidence in scientific research may well be achieved by bringing to bear in systematic concert the scholarly methods of statisticians, philosophers and historians of science, and substantive scientists…” (Allan Birnbaum 1972, p. 861).

“In the training program for PhD students, the relevant basic principles of philosophy of science, methodology, ethics and statistics that enable the responsible practice of science must be covered.” (p. 57, Committee Investigating fraudulent research practices of social psychologist Diederik Stapel)

I was the lone philosophical observer at a special meeting convened by the American Statistical Association (ASA) in 2015 to construct a non-technical document to guide users of statistical significance tests–one of the most common methods used to distinguish genuine effects from chance variability across a landscape of social, physical and biological sciences.

It was, by the ASA Director’s own description, “historical”, but it was also highly philosophical, and its ramifications are only now being discussed and debated. Today, introspection on statistical methods is rather common due to the “statistical crisis in science”. What is it? In a nutshell: high powered computer methods make it easy to arrive at impressive-looking ‘findings’ that too often disappear when others try to replicate them when hypotheses and data analysis protocols are required to be fixed in advance.

*Today is Egon Pearson’s birthday.* In honor of his birthday, I am posting “Statistical Concepts in Their Relation to Reality” (Pearson 1955). I’ve posted it several times over the years, but always find a new gem or two, despite its being so short. E. Pearson rejected some of the familiar tenets that have come to be associated with Neyman and Pearson (N-P) statistical tests, notably the idea that the essential justification for tests resides in a long-run control of rates of erroneous interpretations–what he termed the “behavioral” rationale of tests. In an unpublished letter E. Pearson wrote to Birnbaum (1974), he talks about N-P theory admitting of two interpretations: behavioral and evidential:

“I think you will pick up here and there in my own papers signs of evidentiality, and you can say now that we or I should have stated clearly the difference between the behavioral and evidential interpretations. Certainly we have suffered since in the way the people have concentrated (to an absurd extent often) on behavioral interpretations”.

**Today is Allan Birnbaum’s Birthday. **Birnbaum’s (1962) classic “On the Foundations of Statistical Inference,” in *Breakthroughs in Statistics (volume I 1993), *concerns a principle that remains at the heart of today’s controversies in statistics–even if it isn’t obvious at first: the Likelihood Principle (LP) (also called the strong likelihood Principle SLP, to distinguish it from the weak LP [1]). According to the LP/SLP, given the statistical model, the information from the data are fully contained in the likelihood ratio. Thus, *properties of the sampling distribution of the test statistic vanish *(as I put it in my slides from this post)! But error probabilities are all properties of the sampling distribution. Thus, embracing the LP (SLP) blocks our error statistician’s direct ways of taking into account “biasing selection effects” (slide #10). [Posted earlier here.] Interesting, as seen in a 2018 post on Neyman, Neyman *did* discuss this paper, but had an odd reaction that I’m not sure I understand. (Check it out.) Continue reading

“If a statistical analysis is clearly shown to be effective … it gains nothing from being … principled,” according to Terry Speed in an interesting IMS article (2016) that Harry Crane tweeted about a couple of days ago [i]. Crane objects that you need principles to determine if it is effective, else it “seems that a method is effective (a la Speed) if it gives the answer you want/expect.” I suspected that what Speed was objecting to was an appeal to “principles of inference” of the type to which Neyman objected in my recent post. This turns out to be correct. Here are some excerpts from Speed’s article (emphasis is mine): Continue reading

Categories: Likelihood Principle, Philosophy of Statistics
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I was asked to write something explaining the background of my slides (posted here) in relation to the recent ASA “A World Beyond P-values” conference. I took advantage of some long flight delays on my return to jot down some thoughts:

The contrast between the closing session of the conference “A World Beyond P-values,” and the gist of the conference itself, shines a light on a pervasive tension within the “Beyond P-Values” movement. Two very different debates are taking place. First there’s the debate about how to promote better science. This includes welcome reminders of the timeless demands of rigor and integrity required to avoid deceiving ourselves and others–especially crucial in today’s world of high-powered searches and Big Data. That’s what the closing session was about. [1] Continue reading

Categories: P-values, Philosophy of Statistics, reforming the reformers
9 Comments

Here’s one last entry in honor of Egon Pearson’s birthday: “Statistical Concepts in Their Relation to Reality” (Pearson 1955). I’ve posted it several times over the years (6!), but always find a new gem or two, despite its being so short. E. Pearson rejected some of the familiar tenets that have come to be associated with Neyman and Pearson (N-P) statistical tests, notably the idea that the essential justification for tests resides in a long-run control of rates of erroneous interpretations–what he termed the “behavioral” rationale of tests. In an unpublished letter E. Pearson wrote to Birnbaum (1974), he talks about N-P theory admitting of two interpretations: behavioral and evidential:

“I think you will pick up here and there in my own papers signs of evidentiality, and you can say now that we or I should have stated clearly the difference between the behavioral and evidential interpretations. Certainly we have suffered since in the way the people have concentrated (to an absurd extent often) on behavioral interpretations”.

(Nowadays, some people concentrate to an absurd extent on “science-wise error rates in dichotomous screening”.) Continue reading

*Today is Allan Birnbaum’s birthday. In honor of his birthday, I’m posting the articles in the Synthese volume that was dedicated to his memory in 1977. The editors describe it as their way of “paying homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics”. I paste a few snippets from the articles by Giere and Birnbaum. If you’re interested in statistical foundations, and are unfamiliar with Birnbaum, here’s a chance to catch up. (Even if you are, you may be unaware of some of these key papers.)*

**HAPPY BIRTHDAY ALLAN!**

*Synthese* Volume 36, No. 1 Sept 1977: *Foundations of Probability and Statistics*, Part I

**Editorial Introduction:**

This special issue of

Syntheseon the foundations of probability and statistics is dedicated to the memory of Professor Allan Birnbaum. Professor Birnbaum’s essay ‘The Neyman-Pearson Theory as Decision Theory; and as Inference Theory; with a Criticism of the Lindley-Savage Argument for Bayesian Theory’ was received by the editors ofSynthesein October, 1975, and a decision was made to publish a special symposium consisting of this paper together with several invited comments and related papers. The sad news about Professor Birnbaum’s death reached us in the summer of 1976, but the editorial project could nevertheless be completed according to the original plan. By publishing this special issue we wish to pay homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics. We are grateful to Professor Ronald Giere who wrote an introductory essay on Professor Birnbaum’s concept of statistical evidence and who compiled a list of Professor Birnbaum’s publications.THE EDITORS

Categories: Birnbaum, Likelihood Principle, Statistics, strong likelihood principle
Tags: Birnbaum
1 Comment

Slides from my March 17 presentation on “Severe Testing: The Key to Error Correction” given at the Boston Colloquium for Philosophy of Science Alfred I.Taub forum on “Understanding Reproducibility and Error Correction in Science.”

57th Annual Program

Download the 57th Annual Program

**The Alfred I. Taub forum:**

**UNDERSTANDING REPRODUCIBILITY & ERROR CORRECTION IN SCIENCE**

Cosponsored by GMS and BU’s BEST at Boston University.

Friday, March 17, 2017

1:00 p.m. – 5:00 p.m.

The Terrace Lounge, George Sherman Union

775 Commonwealth Avenue

- Reputation, Variation, &, Control: Historical Perspectives

**Jutta Schickore**History and Philosophy of Science & Medicine, Indiana University, Bloomington. - Crisis in Science: Time for Reform?

**Arturo Casadevall**Molecular Microbiology & Immunology, Johns Hopkins - Severe Testing: The Key to Error Correction

**Deborah Mayo**Philosophy, Virginia Tech - Replicate That…. Maintaining a Healthy Failure Rate in Science

**Stuart Firestein**Biological Sciences, Columbia

**
I. The myth of objectivity.** Whenever you come up against blanket slogans such as “no methods are objective” or “all methods are equally objective and subjective,” it is a good guess that the problem is being trivialized into oblivion. Yes, there are judgments, disagreements, and values in any human activity, which alone makes it too trivial an observation to distinguish among very different ways that threats of bias and unwarranted inferences may be controlled. Is the objectivity-subjectivity distinction really toothless as many will have you believe? I say no.

Cavalier attitudes toward objectivity are in tension with widely endorsed movements to promote replication, reproducibility, and to come clean on a number of sources behind illicit results: multiple testing, cherry picking, failed assumptions, researcher latitude, publication bias and so on. The moves to take back science–if they are not mere lip-service–are rooted in the supposition that we can more objectively scrutinize results,even if it’s only to point out those that are poorly tested. The fact that the term “objectivity” is used equivocally should not be taken as grounds to oust it, but rather to engage in the difficult work of identifying what there is in “objectivity” that we won’t give up, and shouldn’t. Continue reading

Allan Birnbaum died 40 years ago today. He lived to be only 53 [i]. From the perspective of philosophy of statistics and philosophy of science, Birnbaum is best known for his work on likelihood, the Likelihood Principle [ii], and for his attempts to blend concepts of likelihood with error probability ideas to arrive at what he termed “concepts of statistical evidence”. Failing to find adequate concepts of statistical evidence, Birnbaum called for joining the work of “interested statisticians, scientific workers and philosophers and historians of science”–an idea I have heartily endorsed. While known for a result that the (strong) Likelihood Principle followed from sufficiency and conditionality principles (a result that Jimmy Savage deemed one of the greatest breakthroughs in statistics), a few years after publishing it, he turned away from it, perhaps discovering gaps in his argument. A post linking to a 2014 *Statistical Science* issue discussing Birnbaum’s result is here. Reference [5] links to the *Synthese* 1977 volume dedicated to his memory. The editors describe it as their way of “paying homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics”. Ample weekend reading! Continue reading

Categories: Birnbaum, Likelihood Principle, phil/history of stat, Statistics
Tags: Birnbaum
62 Comments

*Today is Allan Birnbaum’s birthday. In honor of his birthday this year, I’m posting the articles in the *Synthese* volume that was dedicated to his memory in 1977. The editors describe it as their way of “paying homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics”. I paste a few snippets from the articles by Giere and Birnbaum. If you’re interested in statistical foundations, and are unfamiliar with Birnbaum, here’s a chance to catch up.(Even if you are,you may be unaware of some of these key papers.)*

**HAPPY BIRTHDAY ALLAN!**

*Synthese* Volume 36, No. 1 Sept 1977: *Foundations of Probability and Statistics*, Part I

**Editorial Introduction:**

This special issue of

Syntheseon the foundations of probability and statistics is dedicated to the memory of Professor Allan Birnbaum. Professor Birnbaum’s essay ‘The Neyman-Pearson Theory as Decision Theory; and as Inference Theory; with a Criticism of the Lindley-Savage Argument for Bayesian Theory’ was received by the editors ofSynthesein October, 1975, and a decision was made to publish a special symposium consisting of this paper together with several invited comments and related papers. The sad news about Professor Birnbaum’s death reached us in the summer of 1976, but the editorial project could nevertheless be completed according to the original plan. By publishing this special issue we wish to pay homage to Professor Birnbaum’s penetrating and stimulating work on the foundations of statistics. We are grateful to Professor Ronald Giere who wrote an introductory essay on Professor Birnbaum’s concept of statistical evidence and who compiled a list of Professor Birnbaum’s publications.THE EDITORS

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