Author: Mayo

Gelman blogged our exchange on abandoning statistical significance

I came across this post on Gelman’s blog today: Exchange with Deborah Mayo on abandoning statistical significance It was straight out of blog comments and email correspondence back when the ASA, and significant others, were rising up against the concept of statistical significance. Here it is: Exchange with Deborah Mayo on abandoning statistical significance Posted […]

(one year ago) RSS 2018 – Significance Tests: Rethinking the Controversy

Here’s what I posted 1 year ago on Aug 30, 2018.   Day 2, Wednesday 05/09/2018 11:20 – 13:20 Keynote 4 – Significance Tests: Rethinking the Controversy Assembly Room Speakers: Sir David Cox, Nuffield College, Oxford Deborah Mayo, Virginia Tech Richard Morey, Cardiff University Aris Spanos, Virginia Tech Intermingled in today’s statistical controversies are some […]

Palavering about Palavering about P-values

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 […]

A. Spanos: Egon Pearson’s Neglected Contributions to Statistics

Continuing with posts on E.S. Pearson in marking his birthday: Egon Pearson’s Neglected Contributions to Statistics by Aris Spanos     Egon Pearson (11 August 1895 – 12 June 1980), is widely known today for his contribution in recasting of Fisher’s significance testing into the Neyman-Pearson (1933) theory of hypothesis testing. Occasionally, he is also credited with […]

Statistical Concepts in Their Relation to Reality–E.S. Pearson

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 […]

S. Senn: Red herrings and the art of cause fishing: Lord’s Paradox revisited (Guest post)

  Stephen Senn Consultant Statistician Edinburgh Background Previous posts[a],[b],[c] of mine have considered Lord’s Paradox. To recap, this was considered in the form described by Wainer and Brown[1], in turn based on Lord’s original formulation: A large university is interested in investigating the effects on the students of the diet provided in the university dining halls […]

Summer Seminar in PhilStat Participants and Special Invited Speakers

Participants in the 2019 Summer Seminar in Philosophy of Statistics   Renée Bolinger, Asst. Professor Dept of Politics and the Center for Human Values, Princeton University (webpage)   Lok Chan, Post Doc Social Science Research Institute, Duke University (webpage)   Marcello Di Bello, Asst. Professor Dept of Philosophy, Lehman College CUNY (webpage)       […]

The NEJM Issues New Guidelines on Statistical Reporting: Is the ASA P-Value Project Backfiring?

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, in my abbreviation) If so, it seems to have backfired. I don’t […]

B. Haig: The ASA’s 2019 update on P-values and significance (ASA II)(Guest Post)

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 […]

SIST: All Excerpts and Mementos: May 2018-July 2019 (updated)

Introduction & Overview The Meaning of My Title: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars* 05/19/18 Blurbs of 16 Tours: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST) 03/05/19   Excursion 1 EXCERPTS Tour I Ex1 TI (full proofs) Excursion 1 Tour I: Beyond Probabilism and Performance: […]

The Statistics Wars: Errors and Casualties

Had I been scheduled to speak later at the 12th MuST Conference & 3rd Workshop “Perspectives on Scientific Error” in Munich, rather than on day 1, I could have (constructively) illustrated some of the errors and casualties by reference to a few of the conference papers that discussed significance tests. (Most gave illuminating discussions of […]

“The 2019 ASA Guide to P-values and Statistical Significance: Don’t Say What You Don’t Mean” (Some Recommendations)

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–opening a special on-line issue of over 40 contributions responding to the […]

SIST: All Excerpts and Mementos: May 2018-May 2019

Introduction & Overview The Meaning of My Title: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars* 05/19/18 Blurbs of 16 Tours: Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (SIST) 03/05/19   Excursion 1 EXCERPTS Tour I Excursion 1 Tour I: Beyond Probabilism and Performance: Severity Requirement (1.1) […]

Excerpts: Final Souvenir Z, Farewell Keepsake & List of Souvenirs

We’ve reached our last Tour (of SIST)*: Pragmatic and Error Statistical Bayesians (Excursion 6), marking the end of our reading with Souvenir Z, the final Souvenir, as well as the Farewell Keepsake in 6.7. Our cruise ship Statinfasst, currently here at Thebes, will be back at dock for maintenance for our next launch at the […]

If you like Neyman’s confidence intervals then you like N-P tests

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 […]