keep meetings hybrid

I was reading the latest ISBA Bulletin and the tribune by ISBA President Sudipto Banerjee celebrating the return to the physical ISBA World meeting, along with worries about participants who caught COVID there. (Unfortunately, one good friend of mine experienced symptoms that went beyond the mild cold-like ones I zoomed through a few days ago.) This particular issue of creating a COVID cluster [during coffee breaks?!] provides [me with] one further argument for my supporting hybrid and multimodal meetings on a general basis. Which should [imho] appear in the proposals for the 2026 and 2028 World Meetings (deadline on 31 October)…(The 2024 meeting in Venezia will certainly involve hybridicity! As will BayesComp in Levi.) Discussing the topic with others in some scientific committees recently made me realise this was not such a shared perspective, from reasons varying from worrying about balancing the budget, to zoom fatigue, to the added value of informal interactions. Still, there also are reasons for hybridising our meetings, from reduced travel impact, to more inclusiveness,  on geographical, diversity, affordability, seniority grounds. Holding hybrid conferences with multiple regional mirrors allows for a potentially higher degree of interaction and local input.  And a minimal organisational effort.

news from ISBA

Some news and reminders from the latest ISBA Bulletin (which also contains an obituary of Don Fraser by Christian Genest):

• Remember that the registration for ISBA 2021 is free till 1 May! The conference is fully online, from 28 June to 2 July
• the Bayesian young statisticians meeting BAYSM 21 will take place online, 1-3 September
• the useR! 2021 conference will also take place online, July 5-9
  
• the MHC2021 (Mixtures, Hidden Markov models, Clustering) conference will take place physically and online at Orsay, France, 2-4 June

eliminating an important obstacle to creative thinking: statistics…

“We hope and anticipate that banning the NHSTP will have the effect of increasing the quality of submitted manuscripts by liberating authors from the stultified structure of NHSTP thinking thereby eliminating an important obstacle to creative thinking.”

About a month ago, David Trafimow and Michael Marks, the current editors of the journal Basic and Applied Social Psychology published an editorial banning all null hypothesis significance testing procedures (acronym-ed into the ugly NHSTP which sounds like a particularly nasty venereal disease!) from papers published by the journal. My first reaction was “Great! This will bring more substance to the papers by preventing significance fishing and undisclosed multiple testing! Power to the statisticians!” However, after reading the said editorial, I realised it was inspired by a nihilistic anti-statistical stance, backed by an apparent lack of understanding of the nature of statistical inference, rather than a call for saner and safer statistical practice. The editors most clearly state that inferential statistical procedures are no longer needed to publish in the journal, only “strong descriptive statistics”. Maybe to keep in tune with the “Basic” in the name of the journal!

“In the NHSTP, the problem is in traversing the distance from the probability of the finding, given the null hypothesis, to the probability of the null hypothesis, given the finding. Regarding confidence intervals, the problem is that, for example, a 95% confidence interval does not indicate that the parameter of interest has a 95% probability of being within the interval.”

The above quote could be a motivation for a Bayesian approach to the testing problem, a revolutionary stance for journal editors!, but it only illustrate that the editors wish for a procedure that would eliminate the uncertainty inherent to statistical inference, i.e., to decision making under… erm, uncertainty: “The state of the art remains uncertain.” To fail to separate significance from certainty is fairly appalling from an epistemological perspective and should be a case for impeachment, were any such thing to exist for a journal board. This means the editors cannot distinguish data from parameter and model from reality! Even more fundamentally, to bar statistical procedures from being used in a scientific study is nothing short of reactionary. While encouraging the inclusion of data is a step forward, restricting the validation or in-validation of hypotheses to gazing at descriptive statistics is many steps backward and does completely jeopardize the academic reputation of the journal, which editorial may end up being the last quoted paper. Is deconstruction now reaching psychology journals?! To quote from a critic of this approach, “Thus, the general weaknesses of the deconstructive enterprise become self-justifying. With such an approach I am indeed not sympathetic.” (Searle, 1983).

“The usual problem with Bayesian procedures is that they depend on some sort of Laplacian assumption to generate numbers where none exist (…) With respect to Bayesian procedures, we reserve the right to make case-by-case judgments, and thus Bayesian procedures are neither required nor banned from BASP.”

The section of Bayesian approaches is trying to be sympathetic to the Bayesian paradigm but again reflects upon the poor understanding of the authors. By “Laplacian assumption”, they mean Laplace´s Principle of Indifference, i.e., the use of uniform priors, which is not seriously considered as a sound principle since the mid-1930’s. Except maybe in recent papers of Trafimow. I also love the notion of “generat[ing] numbers when none exist”, as if the prior distribution had to be grounded in some physical reality! Although it is meaningless, it has some poetic value… (Plus, bringing Popper and Fisher to the rescue sounds like shooting Bayes himself in the foot.)  At least, the fact that the editors will consider Bayesian papers in a case-by-case basis indicate they may engage in a subjective Bayesian analysis of each paper rather than using an automated p-value against the 100% rejection bound!

[Note: this entry was suggested by Alexandra Schmidt, current ISBA President, towards an incoming column on this decision of Basic and Applied Social Psychology for the ISBA Bulletin.]

 

On the Savage Award, advices to Ph.D. candidates [guest post]

This blog post was contributed by my friend Julien Cornebise, as a reprint of a column he wrote for the latest ISBA Bulletin.

This article is an occasion to pay forward ever so slightly, by encouraging current Ph.D. candidates on their path, the support ISBA gave me. Four years ago, I was honored and humbled to receive the ISBA 2010 Savage Award, category Theory and Methods, for my Ph.D. dissertation defended in 2009. Looking back, I can now testify how much this brought to me both inside and outside of Academia.

Inside Academia: confirming and mitigating the widely-shared post-graduate’s impostor syndrome

Upon hearing of the great news, a brilliant multi-awarded senior researcher in my lab very kindly wrote to me that such awards meant never having to prove one’s worth again. Although genuinely touched by her congratulations, being far less accomplished and more junior than her, I felt all the more responsible to prove myself worth of this show of confidence from ISBA. It would be rather awkward to receive such an award only to fail miserably shortly after.

This resonated deeply with the shared secret of recent PhDs, discovered during my year at SAMSI, a vibrant institution where half a dozen new postdocs arrive each year: each and every one of us, fresh Ph.D.s from some of the best institutions (Cambridge, Duke, Waterloo, Paris…) secretly suffered the very same impostor syndrome. We were looking at each other’s CV/website and thinking “jeez! this guy/girl across the door is an expert of his/her field, look at all he/she has done, whereas I just barely scrape by on my own research!” – all the while putting up a convincing façade of self-assurance in front of audiences and whiteboards, to the point of apparent cockiness. Only after candid exchanges in SAMSI’s very open environment did we all discover being in the very same mindset.

In hindsight the explanation is simple: each young researcher in his/her own domain has the very expertise to measure how much he/she still does not know and has yet to learn, while he/she hears other young researchers, experts in their own other field, present results not as familiar to him/her, thus sounding so much more advanced. This take-away from SAMSI was perfectly confirmed by the Savage Award: yes, maybe indeed, I, just like my other colleagues, might actually know something relatively valuable, and my scraping by might just be not so bad – as is also the case of so many of my young colleagues.

Of course, impostor syndrome is a clingy beast and, healthily, I hope to never get entirely over it – merely overcoming it enough to say “Do not worry, thee young candidate, thy doubts pave a path well trodden”.

A similar message is also part of the little-known yet gem of a guide “How to do Research at MIT AI Lab – Emotional Factors”, relevant far beyond its original lab. I recommend it to any Ph.D. student; the feedback from readers is unanimous.

Outside Academia: incredibly increased readability

After two post-docs, and curious to see what was out there in atypical paths, I took a turn out of purely academic research, first as an independent consultant, then recruited out of the blue by a start-up’s recruiter, and eventually doing my small share to help convince investors. I discovered there another facet of ISBA’s Savage Award: tremendous readability.

In Academia, the dominating metric of quality is the length of the publication list – a debate for another day.  Outside of Academia, however, not all interlocutors know how remarkable is a JRSSB Read Paper, or an oral presentation at NIPS, or a publication in Nature.

This is where international learned societies, like ISBA, come into play: the awards they bestow can serve as headline-grabbing material in a biography, easily spotted. The interlocutors do not need to be familiar with the subtleties of Bayesian Analysis. All they see is a stamp of approval from an official association of this researcher’s peers. That, in itself, is enough of a quality metric to pass the first round of contact, raise interest, and get the chance to further the conversation.

First concrete example: the recruiter who contacted me for the start-up I joined in 2011 was tasked to find profiles for an Applied position. The Savage Award on the CV grabbed his attention, even though he had no inkling what Adaptive Sequential Monte Carlo Methods were, nor if they were immediately relevant to the start-up. Passing it to the start-up’s managers, they immediately changed focus and interviewed me for their Research track instead: a profile that was not what they were looking for originally, yet stood out enough to interest them for a position they had not thought of filling via a recruiter – and indeed a unique position that I would never have thought to find this way either!

Second concrete example, years later, hard at work in this start-up’s amazing team: investors were coming for a round of technical due diligence. Venture capitals sent their best scientists-in-residence to dive deeply into the technical details of our research. Of course what matters in the end is, and forever will be, the work that is done and presented. Yet, the Savage Award was mentioned in the first line of the biography that was sent ahead of time, as a salient point to give a strong first impression of our research team.

Advices to Ph.D. Candidates: apply, you are the world best expert on your topic

That may sound trivial, but the first advice: apply. Discuss with your advisor the possibility to put your dissertation up for consideration. This might sound obvious to North-American students, whose educative system is rife with awards for high-performing students. Not so much in France, where those would be at odds with the sometimes over-present culture of égalité in the younger-age public education system. As a cultural consequence, few French Ph.D. students, even the most brilliant, would consider putting up their dissertation for consideration. I have been very lucky in that regard to benefit from the advice of a long-term Bayesian, who offered to send it for me – thanks again Xi’an! Not all students, regardless how brilliant their work, are made aware of this possibility.

The second advice, closely linked: do not underestimate the quality of your work. You are the foremost expert in the entire world on your Ph.D. topic. As discussed above, it is all too easy to see how advanced are the maths wielded by your office-mate, yet oversee the as-much-advanced maths you are juggling on a day-to-day basis, more familiar to you, and whose limitations you know better than anyone else. Actually, knowing these very limitations is what proves you are an expert.

A word of thanks and final advice

Finally, a word of thanks. I have been incredibly lucky, throughout my career so far, to meet great people. My dissertation already had four pages of acknowledgements: I doubt the Bulletin’s editor would appreciate me renewing (and extending!) them here. They are just as heartfelt today as they were then. I must, of course, add ISBA and the Savage Award committee for their support, as well as all those who, by their generous donations, allow the Savage Fund to stay alive throughout the years.

Of interest to Ph.D. candidates, though, one special mention of a dual tutelage system, that I have seen successfully at work many times. The most senior, a professor with the deep knowledge necessary to steer the project brings his endless fonts of knowledge collected over decades, wrapped in hardened tough-love. The youngest, a postdoc or fresh assistant professor, brings virtuosity, emulation and day-to-day patience. In my case they were Pr. Éric Moulines and Dr. Jimmy Olsson. That might be the final advice to a student: if you ever stumble, as many do, as I most surely did, because Ph.D. studies can be a hell of a roller-coaster to go through, reach out to the people around you and the joint set of skills they want to offer you. In combination, they can be amazing, and help you open doors that, in retrospect, can be worth all the efforts.

Julien Cornebise, Ph.D.
www.cornebise.com/julien

 

books versus papers [for PhD students]

Before I run out of time, here is my answer to the ISBA Bulletin Students’ corner question of the term: “In terms of publications and from your own experience, what are the pros and cons of books vs journal articles?“

While I started on my first book during my postdoctoral years in Purdue and Cornell [a basic probability book made out of class notes written with Arup Bose, which died against the breakers of some referees’ criticisms], my overall opinion on this is that books are never valued by hiring and promotion committees for what they are worth! It is a universal constant I met in the US, the UK and France alike that books are not helping much for promotion or hiring, at least at an early stage of one’s career. Later, books become a more acknowledge part of senior academics’ vitae. So, unless one has a PhD thesis that is ready to be turned into a readable book without having any impact on one’s publication list, and even if one has enough material and a broad enough message at one’s disposal, my advice is to go solely and persistently for journal articles. Besides the above mentioned attitude of recruiting and promotion committees, I believe this has several positive aspects: it forces the young researcher to maintain his/her focus on specialised topics in which she/he can achieve rapid prominence, rather than having to spend [quality research] time on replacing the background and building reference. It provides an evaluation by peers of the quality of her/his work, while reviews of books are generally on the light side. It is the starting point for building a network of collaborations, few people are interested in writing books with strangers (when knowing it is already quite a hardship with close friends!). It is also the entry to workshops and international conferences, where a new book very rarely attracts invitations.

Writing a book is of course exciting and somewhat more deeply rewarding, but it is awfully time-consuming and requires a high level of organization young faculty members rarely possess when starting a teaching job at a new university (with possibly family changes as well!). I was quite lucky when writing The Bayesian Choice and Monte Carlo Statistical Methods to mostly be on leave from teaching, as it would have otherwise be impossible! That we are not making sufficient progress on our revision of Bayesian Core, started two years ago, is a good enough proof that even with tight planning, great ideas, enthusiasm, sale prospects, and available material, completing a book may get into trouble for mere organisational issues…