5 September, 2018 (w/updates) RSS 2018 – Significance Tests: Rethinking the Controversy


Day 2, Wed 5th September, 2018:

The 2018 Meeting of the Royal Statistical Society (Cardiff)

11:20 – 13:20

Keynote 4 – Significance Tests: Rethinking the Controversy Assembly Room

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 long-standing, but unresolved, disagreements on the nature and principles of statistical methods and the roles for probability in statistical inference and modelling. In reaction to the so-called “replication crisis” in the sciences, some reformers suggest significance tests as a major culprit. To understand the ramifications of the proposed reforms, there is a pressing need for a deeper understanding of the source of the problems in the sciences and a balanced critique of the alternative methods being proposed to supplant significance tests. In this session speakers offer perspectives on significance tests from statistical science, econometrics, experimental psychology and philosophy of science. There will be also be panel discussion.

5 Sept. 2018 (taken by A.Spanos)

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The Physical Reality of My New Book! Here at the RSS Meeting (2 years ago)


You can find several excerpts and mementos from the book, including whole “tours” (in proofs) updated June 2020 here.

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Statistical Crises and Their Casualties–what are they?

What do I mean by “The Statistics Wars and Their Casualties”? It is the title of the workshop I have been organizing with Roman Frigg at the London School of Economics (CPNSS) [1], which was to have happened in June. It is now the title of a forum I am zooming on Phil Stat that I hope you will want to follow. It’s time that I explain and explore some of the key facets I have in mind with this title. Continue reading

Categories: Error Statistics | 4 Comments

New Forum on The Statistics Wars & Their Casualties: August 20, Preregistration (D. Lakens)

I will now hold a monthly remote forum on Phil Stat: The Statistics Wars and Their Casualties–the title of the workshop I had scheduled to hold at the London School of Economics (Centre for Philosophy of Natural and Social Science: CPNSS) on 19-20 June 2020. (See the announcement at the bottom of this blog). I held the graduate seminar in Philosophy (PH500) that was to precede the workshop remotely (from May 21-June 25), and this new forum will be both an extension of that and a linkage to the planned workshop. The issues are too pressing to put off for a future in-person workshop, which I still hope to hold. It will begin with presentations by workshop participants, with lots of discussion. If you want to be part of this monthly forum and engage with us, please go to the information and directions page. The links are now fixed, sorry. (It also includes readings for Aug 20.)  If you are already on our list, you’ll automatically be notified of new meetings. (If you have questions, email me.) Continue reading

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August 6: JSM 2020 Panel on P-values & “Statistical Significance”


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):

Categories: ASA Guide to P-values, Error Statistics, evidence-based policy, JSM 2020, P-values, Philosophy of Statistics, science communication, significance tests | 3 Comments

JSM 2020 Panel on P-values & “Statistical Significance”

All: On July 30 (10am EST) I will give a virtual version of my JSM presentation, remotely like the one I will actually give on Aug 6 at the JSM. Co-panelist Stan Young may as well. One of our surprise guests tomorrow (not at the JSM) will be Yoav Benjamini!  If you’re interested in attending our July 30 practice session* please follow the directions here. Background items for this session are in the “readings” and “memos” of session 5.

*unless you’re already on our LSE Phil500 list

JSM 2020 Panel Flyer (PDF)
JSM online program w/panel abstract & information): Continue reading

Categories: Announcement, JSM 2020, significance tests, stat wars and their casualties | Leave a comment

Stephen Senn: Losing Control (guest post)


Stephen Senn
Consultant Statistician

Losing Control

Match points

The idea of local control is fundamental to the design and analysis of experiments and contributes greatly to a design’s efficiency. In clinical trials such control is often accompanied by randomisation and the way that the randomisation is carried out has a close relationship to how the analysis should proceed. For example, if a parallel group trial is carried out in different centres, but randomisation is ‘blocked’ by centre then, logically, centre should be in the model (Senn, S. J. & Lewis, R. J., 2019). On the other hand if all the patients in a given centre are allocated the same treatment at random, as in a so-called cluster randomised trial, then the fundamental unit of inference becomes the centre and patients are regarded as repeated measures on it. In other words, the way in which the allocation has been carried out effects the degree of matching that has been achieved and this, in turn, is related to the analysis that should be employed. A previous blog of mine, To Infinity and Beyond,  discusses the point. Continue reading

Categories: covid-19, randomization, RCTs, S. Senn | 14 Comments

JSM 2020: P-values & “Statistical Significance”, August 6

Link: https://ww2.amstat.org/meetings/jsm/2020/onlineprogram/ActivityDetails.cfm?SessionID=219596

To register for JSM: https://ww2.amstat.org/meetings/jsm/2020/registration.cfm

Categories: JSM 2020, P-values | Leave a comment

Colleges & Covid-19: Time to Start Pool Testing


I. “Colleges Face Rising Revolt by Professors,” proclaims an article in today’s New York Times, in relation to returning to in-person teaching:

Thousands of instructors at American colleges and universities have told administrators in recent days that they are unwilling to resume in-person classes because of the pandemic. More than three-quarters of colleges and universities have decided students can return to campus this fall. But they face a growing faculty revolt.
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Categories: covid-19 | Tags: | 8 Comments

David Hand: Trustworthiness of Statistical Analysis (LSE PH 500 presentation)

This was David Hand’s guest presentation (25 June) at our zoomed graduate research seminar (LSE PH500) on Current Controversies in Phil Stat (~30 min.)  I’ll make some remarks in the comments, and invite yours.


Trustworthiness of Statistical Analysis

David Hand

Abstract: Trust in statistical conclusions derives from the trustworthiness of the data and analysis methods. Trustworthiness of the analysis methods can be compromised by misunderstanding and incorrect application. However, that should stimulate a call for education and regulation, to ensure that methods are used correctly. The alternative of banning potentially useful methods, on the grounds that they are often misunderstood and misused is short-sighted, unscientific, and Procrustean. It damages the capability of science to advance, and feeds into public mistrust of the discipline.

Below are Prof.Hand’s slides w/o audio, followed by a video w/audio. You can also view them on the Meeting #6 post on the PhilStatWars blog (https://phil-stat-wars.com/2020/06/21/meeting-6-june-25/). Continue reading

Categories: LSE PH 500 | Tags: , , , , , , | 7 Comments

Bonus meeting: Graduate Research Seminar: Current Controversies in Phil Stat: LSE PH 500: 25 June 2020

Ship StatInfasSt

We’re holding a bonus, 6th, meeting of the graduate research seminar PH500 for the Philosophy, Logic & Scientific Method Department at the LSE:

(Remote 10am-12 EST, 15:00 – 17:00 London time; Thursday, June 25)

VI. (June 25) BONUS: Power, shpower, severity, positive predictive value (diagnostic model) & a Continuation of The Statistics Wars and Their Casualties

There will also be a guest speaker: Professor David Hand (Imperial College, London). Here is Professor Hand’s presentation (click on “present” to hear sound)

The main readings are on the blog page for the seminar.


Categories: Graduate Seminar PH500 LSE, power | Leave a comment

“On the Importance of testing a random sample (for Covid)”, an article from Significance magazine


Nearly 3 months ago I tweeted “Stat people: shouldn’t they be testing a largish random sample of people [w/o symptoms] to assess rates, alert those infected, rather than only high risk, symptomatic people, in the U.S.?” I was surprised that nearly all the stat and medical people I know expressed the view that it wouldn’t be feasible or even very informative. Really? Granted, testing was and is limited, but had it been made a priority, it could have been done. In the new issue of Significance (June 2020) that I just received, James J. Cochran writes “on the importance of testing a random sample.” [1] 

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Categories: random sample | 13 Comments

Birthday of Allan Birnbaum: Foundations of Probability and Statistics (27 May 1923 – 1 July 1976)

27 May 1923-1 July 1976

27 May 1923-1 July 1976

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: | 3 Comments

Graduate Research Seminar: Current Controversies in Phil Stat: LSE PH 500: 21 May – 18 June 2020


Ship StatInfasST will embark on a new journey from 21 May – 18 June, a graduate research seminar for the Philosophy, Logic & Scientific Method Department at the LSE, but given the pandemic has shut down cruise ships, it will remain at dock in the U.S. and use zoom. If you care to follow any of the 5 sessions, nearly all of the materials will be linked here collected from excerpts already on this blog. If you are interested in observing on zoom beginning 28 May, please follow the directions here

For the updated schedule, see the seminar web page.

Topic: Current Controversies in Phil Stat
(LSE, Remote 10am-12 EST, 15:00 – 17:00 London time; Thursdays 21 May-18 June) Continue reading

Categories: Announcement, SIST | Leave a comment

Final part of B. Haig’s ‘What can psych stat reformers learn from the error-stat perspective?’ (Bayesian stats)


Here’s the final part of Brian Haig’s recent paper ‘What can psychology’s statistics reformers learn from the error-statistical perspective?’ in Methods in Psychology 2 (Nov. 2020). The full article, which is open access, is here. I will make some remarks in the comments.

5. The error-statistical perspective and the nature of science


As noted at the outset, the error-statistical perspective has made significant contributions to our philosophical understanding of the nature of science. These are achieved, in good part, by employing insights about the nature and place of statistical inference in experimental science. The achievements include deliberations on important philosophical topics, such as the demarcation of science from non-science, the underdetermination of theories by evidence, the nature of scientific progress, and the perplexities of inductive inference. In this article, I restrict my attention to two such topics: The process of falsification and the structure of modeling.

5.1. Falsificationism Continue reading

Categories: Brian Haig, SIST | 3 Comments

Part 2 of B. Haig’s ‘What can psych stat reformers learn from the error-stat perspective?’ (Bayesian stats)


Here’s a picture of ripping open the first box of (rush) copies of Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars*, and here’s a continuation of Brian Haig’s recent paper ‘What can psychology’s statistics reformers learn from the error-statistical perspective?’ in Methods in Psychology 2 (Nov. 2020). Haig contrasts error statistics, the “new statistics”, and Bayesian statistics from the perspective of the statistics wars in psychology. The full article, which is open access, is here. I will make several points in the comments.


4. Bayesian statistics

Despite its early presence, and prominence, in the history of statistics, the Bayesian outlook has taken an age to assert itself in psychology. However, a cadre of methodologists has recently advocated the use of Bayesian statistical methods as a superior alternative to the messy frequentist practice that dominates psychology’s research landscape (e.g., Dienes, 2011; Kruschke and Liddell, 2018; Wagenmakers, 2007). These Bayesians criticize NHST, often advocate the use of Bayes factors for hypothesis testing, and rehearse a number of other well-known Bayesian objections to frequentist statistical practice. Continue reading

Categories: Brian Haig, SIST | 6 Comments

‘What can psychology’s statistics reformers learn from the error-statistical perspective?’


This is the title of Brian Haig’s recent paper in Methods in Psychology 2 (Nov. 2020). Haig is a professor emeritus of psychology at the University of Canterbury. Here he provides both a thorough and insightful review of my book Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (CUP, 2018) as well as an excellent overview of the high points of today’s statistics wars and the replication crisis, especially from the perspective of psychology. I’ll excerpt from his article in a couple of posts. The full article, which is open access, is here

Abstract: In this article, I critically evaluate two major contemporary proposals for reforming statistical thinking in psychology: The recommendation that psychology should employ the “new statistics” in its research practice, and the alternative proposal that it should embrace Bayesian statistics. I do this from the vantage point of the modern error-statistical perspective, which emphasizes the importance of the severe testing of knowledge claims. I also show how this error-statistical perspective improves our understanding of the nature of science by adopting a workable process of falsification and by structuring inquiry in terms of a hierarchy of models. Before concluding, I briefly discuss the importance of the philosophy of statistics for improving our understanding of statistical thinking.

Brian Haig

Keywords: The error-statistical perspective, The new statistics, Bayesian statistics, Falsificationism, Hierarchy of models, Philosophy of statistics Continue reading

Categories: Brian Haig, Statistical Inference as Severe Testing–Review | 12 Comments

S. Senn: Randomisation is not about balance, nor about homogeneity but about randomness (Guest Post)


Stephen Senn
Consultant Statistician

The intellectual illness of clinical drug evaluation that I have discussed here can be cured, and it will be cured when we restore intellectual primacy to the questions we ask, not the methods by which we answer them. Lewis Sheiner1

Cause for concern

In their recent essay Causal Evidence and Dispositions in Medicine and Public Health2, Elena Rocca and Rani Lill Anjum challenge, ‘the epistemic primacy of randomised controlled trials (RCTs) for establishing causality in medicine and public health’. That an otherwise stimulating essay by two philosophers, experts on causality, which makes many excellent points on the nature of evidence, repeats a common misunderstanding about randomised clinical trials, is grounds enough for me to address this topic again.  Before, however, explaining why I disagree with Rocca and Anjum on RCTs, I want to make clear that I agree with much of what they say. I loathe these pyramids of evidence, beloved by some members of the evidence-based movement, which have RCTs at the apex or possibly occupying a second place just underneath meta-analyses of RCTs. In fact, although I am a great fan of RCTs and (usually) of intention to treat analysis, I am convinced that RCTs alone are not enough. My thinking on this was profoundly affected by Lewis Sheiner’s essay of nearly thirty years ago (from which the quote at the beginning of this blog is taken). Lewis was interested in many aspects of investigating the effects of drugs and would, I am sure, have approved of Rocca and Anjum’s insistence that there are many layers of understanding how and why things work, and that means of investigating them may have to range from basic laboratory experiments to patient narratives via RCTs. Rocca and Anjum’s essay provides a good discussion of the various ‘causal tasks’ that need to be addressed and backs this up with some excellent examples. Continue reading

Categories: RCTs, S. Senn | 29 Comments

Paradigm Shift in Pandemic (Vent) Protocols?

Lung Scans[0]

As much as doctors and hospitals are raising alarms about a shortage of ventilators for Covid-19 patients, some doctors have begun to call for entirely reassessing the standard paradigm for their use–according to a cluster of articles to appear in the last week. “What’s driving this reassessment is a baffling observation about Covid-19: Many patients have blood oxygen levels so low they should be dead. But they’re not gasping for air, their hearts aren’t racing, and their brains show no signs of blinking off from lack of oxygen.”[1] Within that group of patients, some doctors wonder if the standard use of mechanical ventilators does more harm than good.[2] The issue is controversial; I’ll just report what I find in the articles over the past week. Please share ongoing updates in the comments. Continue reading

Categories: covid-19 | 62 Comments

A. Spanos:  Isaac Newton and his two years in quarantine:  how science could germinate in bewildering ways (Guest post)


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

Beyond the plenitude of misery and suffering that pandemics bring down on humanity, occasionally they contribute to the betterment of humankind by (inadvertently) boosting creative activity that leads to knowledge, and not just in epidemiology. A case in point is that of Isaac Newton and the pandemic of 1665-6.  Continue reading

Categories: quarantine, Spanos | 14 Comments

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