A. Spanos: Jerzy Neyman and his Enduring Legacy (guest post)

I am reblogging a guest post that Aris Spanos wrote for this blog on Neyman’s birthday some years ago.   

A. Spanos

A Statistical Model as a Chance Mechanism
Aris Spanos 

Jerzy Neyman (April 16, 1894 – August 5, 1981), was a Polish/American statistician[i] who spent most of his professional career at the University of California, Berkeley. Neyman is best known in statistics for his pioneering contributions in framing the Neyman-Pearson (N-P) optimal theory of hypothesis testing and his theory of Confidence Intervals. (This article was first posted here.) Continue reading

Categories: Neyman, Spanos | Leave a comment

Happy Birthday Neyman: What was Neyman opposing when he opposed the ‘Inferential’ Probabilists?

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Today is Jerzy Neyman’s birthday (April 16, 1894 – August 5, 1981). I’m posting a link to a quirky paper of his that explains one of the most misunderstood of his positions–what he was opposed to in opposing the “inferential theory”. The paper is Neyman, J. (1962), ‘Two Breakthroughs in the Theory of Statistical Decision Making‘ [i] It’s chock full of ideas and arguments. “In the present paper” he tells us, “the term ‘inferential theory’…will be used to describe the attempts to solve the Bayes’ problem with a reference to confidence, beliefs, etc., through some supplementation …either a substitute a priori distribution [exemplified by the so called principle of insufficient reason] or a new measure of uncertainty” such as Fisher’s fiducial probability. It arises on p. 391 of Excursion 5 Tour III of Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018, CUP). Here’s a link to the proofs of that entire tour. If you hear Neyman rejecting “inferential accounts” you have to understand it in this very specific way: he’s rejecting “new measures of confidence or diffidence”. Here he alludes to them as “easy ways out”. He is not rejecting statistical inference in favor of behavioral performance as typically thought. Neyman always distinguished his error statistical performance conception from Bayesian and Fiducial probabilisms [ii]. The surprising twist here is semantical and the culprit is none other than…Allan Birnbaum. Yet Birnbaum gets short shrift, and no mention is made of our favorite “breakthrough” (or did I miss it?). You can find quite a lot on this blog searching Birnbaum. Continue reading

Categories: Bayesian/frequentist, Error Statistics, Neyman | 3 Comments

Intellectual conflicts of interest: Reviewers

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Where do journal editors look to find someone to referee your manuscript (in the typical “double blind” review system in academic journals)? One obvious place to look is the reference list in your paper. After all, if you’ve cited them, they must know about the topic of your paper, putting them in a good position to write a useful review. The problem is that if your paper is on a topic of ardent disagreement, and you argue in favor of one side of the debates, then your reference list is likely to include those with actual or perceived conflicts of interest. After all, if someone has a strong standpoint on an issue of some controversy, and a strong interest in persuading others to accept their side, it creates an intellectual conflict of interest, if that person has power to uphold that view. Since your referee is in a position of significant power to do just that, it follows that they have a conflict of interest (COI). A lot of attention is paid to author’s conflicts of interest, but little into intellectual or ideological conflicts of interests of reviewers. At most, the concern is with the reviewer having special reasons to favor the author, usually thought to be indicated by having been a previous co-author. We’ve been talking about journal editors conflicts of interest as of late (e.g., with Mark Burgman’s presentation at the last Phil Stat Forum) and this brings to mind another one. Continue reading

Categories: conflicts of interest, journal referees | 12 Comments

ASA to Release the Recommendations of its Task Force on Statistical Significance and Replication

The American Statistical Association has announced that it has decided to reverse course and share the recommendations developed by the ASA Task Force on Statistical Significance and Replicability in one of its official channels. The ASA Board created this group [1] in November 2019 “with a charge to develop thoughtful principles and practices that the ASA can endorse and share with scientists and journal editors.” (AMSTATNEWS 1 February 2020). Some members of the ASA Board felt that its earlier decision not to make these recommendations public, but instead to leave the group to publish its recommendations on its own, might give the appearance of a conflict of interest between the obligation of the ASA to represent the wide variety of methodologies used by its members in widely diverse fields, and the advocacy by some members who believe practitioners should stop using the term “statistical significance” and end the practice of using p-value thresholds in interpreting data [the Wasserstein et al. (2019) editorial]. I think that deciding to publicly share the new Task Force recommendations is very welcome, given especially that the Task Force was appointed to avoid just such an apparent conflict of interest. Past ASA President, Karen Kafadar noted: Continue reading

Categories: conflicts of interest | 1 Comment

The Stat Wars and Intellectual conflicts of interest: Journal Editors

 

Like most wars, the Statistics Wars continues to have casualties. Some of the reforms thought to improve reliability and replication may actually create obstacles to methods known to improve on reliability and replication. At each one of our meeting of the Phil Stat Forum: “The Statistics Wars and Their Casualties,” I take 5 -10 minutes to draw out a proper subset of casualties associated with the topic of the presenter for the day. (The associated workshop that I have been organizing with Roman Frigg at the London School of Economics (CPNSS) now has a date for a hoped for in-person meeting in London: 24-25 September 2021.) Of course we’re interested not just in casualties but in positive contributions, though what counts as a casualty and what a contribution is itself a focus of philosophy of statistics battles.

Continue reading
Categories: Error Statistics | Leave a comment

Reminder: March 25 “How Should Applied Science Journal Editors Deal With Statistical Controversies?” (Mark Burgman)

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

Categories: ASA Guide to P-values, confidence intervals and tests, P-values, significance tests | Tags: , | 1 Comment

Pandemic Nostalgia: The Corona Princess: Learning from a petri dish cruise (reblog 1yr)

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Last week, giving a long postponed talk for the NY/NY Metro Area Philosophers of Science Group (MAPS), I mentioned how my book Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (2018, CUP) invites the reader to see themselves on a special interest cruise as we revisit old and new controversies in the philosophy of statistics–noting that I had no idea in writing the book that cruise ships would themselves become controversial in just a few years. The first thing I wrote during early pandemic days last March was this post on the Diamond Princess. The statistics gleaned from the ship remain important resources which haven’t been far off in many ways. I reblog it here. Continue reading

Categories: covid-19, memory lane | Leave a comment

March 25 “How Should Applied Science Journal Editors Deal With Statistical Controversies?” (Mark Burgman)

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

Categories: ASA Guide to P-values, confidence intervals and tests, P-values, significance tests | Tags: , | 1 Comment

Falsifying claims of trust in bat coronavirus research: mysteries of the mine (i)-(iv)

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Have you ever wondered if people read Master’s (or even Ph.D) theses a decade out? Whether or not you have, I think you will be intrigued to learn the story of why an obscure Master’s thesis from 2012, translated from Chinese in 2020, is now an integral key for unravelling the puzzle of the global controversy about the mechanism and origins of Covid-19. The Master’s thesis by a doctor, Li Xu [1], “The Analysis of 6 Patients with Severe Pneumonia Caused by Unknown Viruses”, describes 6 patients he helped to treat after they entered a hospital in 2012, one after the other, suffering from an atypical pneumonia from cleaning up after bats in an abandoned copper mine in China. Given the keen interest in finding the origin of the 2002–2003 severe acute respiratory syndrome (SARS) outbreak, Li wrote: “This makes the research of the bats in the mine where the six miners worked and later suffered from severe pneumonia caused by unknown virus a significant research topic”. He and the other doctors treating the mine cleaners hypothesized that their diseases were caused by a SARS-like coronavirus from having been in close proximity to the bats in the mine. Continue reading

Categories: covid-19, falsification, science communication | 23 Comments

Aris Spanos: Modeling vs. Inference in Frequentist Statistics (guest post)

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Aris Spanos
Wilson Schmidt Professor of Economics
Department of Economics
Virginia Tech

The following guest post (link to updated PDF) was written in response to C. Hennig’s presentation at our Phil Stat Wars Forum on 18 February, 2021: “Testing With Models That Are Not True”. Continue reading

Categories: misspecification testing, Spanos, stat wars and their casualties | 11 Comments

R.A. Fisher: “Statistical methods and Scientific Induction” with replies by Neyman and E.S. Pearson

In Recognition of Fisher’s birthday (Feb 17), I reblog his contribution to the “Triad”–an exchange between  Fisher, Neyman and Pearson 20 years after the Fisher-Neyman break-up. The other two are below. My favorite is the reply by E.S. Pearson, but all are chock full of gems for different reasons. They are each very short and are worth your rereading. Continue reading

Categories: E.S. Pearson, Fisher, Neyman, phil/history of stat | Leave a comment

R. A. Fisher: How an Outsider Revolutionized Statistics (Aris Spanos)

A SPANOS

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This is a belated birthday post for R.A. Fisher (17 February, 1890-29 July, 1962)–it’s a guest post from earlier on this blog by Aris Spanos that has gotten the highest number of hits over the years. 

Happy belated birthday to R.A. Fisher!

‘R. A. Fisher: How an Outsider Revolutionized Statistics’

by Aris Spanos

Few statisticians will dispute that R. A. Fisher (February 17, 1890 – July 29, 1962) is the father of modern statistics; see Savage (1976), Rao (1992). Inspired by William Gosset’s (1908) paper on the Student’s t finite sampling distribution, he recast statistics into the modern model-based induction in a series of papers in the early 1920s. He put forward a theory of optimal estimation based on the method of maximum likelihood that has changed only marginally over the last century. His significance testing, spearheaded by the p-value, provided the basis for the Neyman-Pearson theory of optimal testing in the early 1930s. According to Hald (1998) Continue reading

Categories: Fisher, phil/history of stat, Spanos | 2 Comments

Reminder: February 18 “Testing with models that are not true” (Christian Hennig)

The sixth meeting of our Phil Stat Forum*:

The Statistics Wars
and Their Casualties

18 February, 2021

TIME: 15:00-16:45 (London); 10-11:45 a.m. (New York, EST)

For information about the Phil Stat Wars forum and how to join, click on this link. 

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Testing with Models that Are Not True Continue reading

Categories: Phil Stat Forum | Leave a comment

S. Senn: The Power of Negative Thinking (guest post)

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Stephen Senn
Consultant Statistician
Edinburgh, Scotland

Sepsis sceptic

During an exchange on Twitter, Lawrence Lynn drew my attention to a paper by Laffey and Kavanagh[1]. This makes an interesting, useful and very depressing assessment of the situation as regards clinical trials in critical care. The authors make various claims that RCTs in this field are not useful as currently conducted. I don’t agree with the authors’ logic here although, perhaps, surprisingly, I consider that their conclusion might be true. I propose to discuss this here. Continue reading

Categories: power, randomization | 5 Comments

February 18 “Testing with models that are not true” (Christian Hennig)

The sixth meeting of our Phil Stat Forum*:

The Statistics Wars
and Their Casualties

18 February, 2021

TIME: 15:00-16:45 (London); 10-11:45 a.m. (New York, EST)

For information about the Phil Stat Wars forum and how to join, click on this link. 

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Testing with Models that Are Not True

Christian Hennig

Continue reading

Categories: Phil Stat Forum | 1 Comment

The Covid-19 Mask Wars : Hi-Fi Mask Asks

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Effective yesterday, February 1, it is a violation of federal law not to wear a mask on a public conveyance or in a transit hub, including taxis, trains and commercial trucks (The 11 page mandate is here.)

The “mask wars” are a major source of disagreement and politicizing science during the current pandemic, but my interest here is not of clashes between pro-and anti-mask culture warriors, but the clashing recommendations among science policy officials and scientists wearing their policy hats. A recent Washington Post editorial by Joseph Allen, (director of the Healthy Buildings program at the Harvard T.H. Chan School of Public Health), declares “Everyone should be wearing N95 masks now”. In his view: Continue reading

Categories: covid-19 | 27 Comments

January 28 Phil Stat Forum “How Can We Improve Replicability?” (Alexander Bird)

The fifth meeting of our Phil Stat Forum*:

The Statistics Wars
and Their Casualties

28 January, 2021

TIME: 15:00-16:45 (London); 10-11:45 a.m. (New York, EST)

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“How can we improve replicability?”

Alexander Bird 

Continue reading

Categories: Phil Stat Forum | 1 Comment

S. Senn: “Beta testing”: The Pfizer/BioNTech statistical analysis of their Covid-19 vaccine trial (guest post)

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Stephen Senn

Consultant Statistician
Edinburgh, Scotland

The usual warning

Although I have researched on clinical trial design for many years, prior to the COVID-19 epidemic I had had nothing to do with vaccines. The only object of these amateur musings is to amuse amateurs by raising some issues I have pondered and found interesting. Continue reading

Categories: covid-19, PhilStat/Med, S. Senn | 16 Comments

Why hasn’t the ASA Board revealed the recommendations of its new task force on statistical significance and replicability?

something’s not revealed

A little over a year ago, the board of the American Statistical Association (ASA) appointed a new Task Force on Statistical Significance and Replicability (under then president, Karen Kafadar), to provide it with recommendations. [Its members are here (i).] You might remember my blogpost at the time, “Les Stats C’est Moi”. The Task Force worked quickly, despite the pandemic, giving its recommendations to the ASA Board early, in time for the Joint Statistical Meetings at the end of July 2020. But the ASA hasn’t revealed the Task Force’s recommendations, and I just learned yesterday that it has no plans to do so*. A panel session I was in at the JSM, (P-values and ‘Statistical Significance’: Deconstructing the Arguments), grew out of this episode, and papers from the proceedings are now out. The introduction to my contribution gives you the background to my question, while revealing one of the recommendations (I only know of 2). Continue reading

Categories: 2016 ASA Statement on P-values, JSM 2020, replication crisis, statistical significance tests, straw person fallacy | 8 Comments

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

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Continue reading
Categories: Birnbaum, Birnbaum Brakes, Likelihood Principle | 5 Comments

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