Archive for Andrew Gelman

perspectives on Deborah Mayo’s Statistics Wars

Posted in Statistics with tags , , , , on October 23, 2019 by xi'an

A few months ago, Andrew Gelman collated and commented the reviews of Deborah Mayo’s book by himself, Brian Haig, Christian Hennig, Art B. Owen, Robert Cousins, Stan Young, Corey Yanofsky, E.J. Wagenmakers, Ron Kenett, Daniel Lakeland, and myself. The collection did not make it through the review process of the Harvard Data Science Review! it is however available on-line for perusal…

No review this summer

Posted in Books, Statistics, University life with tags , , , , , , , , on September 19, 2019 by xi'an

A recent editorial in Nature was a declaration by a biologist from UCL on her refusal to accept refereeing requests during the summer (or was it the summer break), which was motivated by a need to reconnect with her son. Which is a good enough reason (!), but reflects sadly on the increasing pressure on one’s schedule to juggle teaching, research, administration, grant hunting, society service, along with a balanced enough family life. (Although I have been rather privileged in this regard!) Given that refereeing or journal editing is neither visible nor rewarded, it comes as the first task to be postponed or abandoned, even though most of us realise it is essential to keep science working as a whole and to make our own papers published. I have actually noticed an increasing difficulty in the past decade to get (good) referees to accept new reviews, often asking for deadlines that are hurting the authors, like six months. Making them practically unavailable. As I mentioned earlier on this blog, it could be that publishing referees’ reports as discussions would help, since they would become recognised as (unreviewed!) publications, but it is unclear this is the solution. If judging from the similar difficulty in getting discussions for discussed papers. (As an aside, there are two exciting papers coming up for discussion in Series B, ‘Unbiased Markov chain Monte Carlo methods with couplings’ by  Pierre E. Jacob, John O’Leary and Yves F. Atchadé and in Bayesian Analysis, Latent nested nonparametric priors by Frederico Camerlenghi, David Dunson, Antonio Lijoi, Igor Prünster, and Abel Rodríguez). Which is surprising when considering the willingness of a part of the community to engage into forii discussions, sometimes of a considerable length as illustrated on Andrew’s blog.

Another entry in Nature mentioned the case of two University of København tenured professors in geology who were fired for either using a private email address (?!) or being away on field work during an exam and at a conference without permission from the administration. Which does not even remotely sound like a faulty behaviour to me or else I would have been fired eons ago..!

a chance (?) encounter

Posted in Kids, pictures, Travel with tags , , , , , on July 16, 2019 by xi'an

As I was cycling to Paris Dauphine, a few days ago, I spotted someone sitting on a bench and working on a laptop who suspiciously looked like… Andrew Gelman! As I knew Andrew was in Paris that week, and as we were reasonably close to Dauphine, this did not sound like a zero probability event. I thus stopped to check that indeed this was the real Andrew, who happened to be in the vicinity and had decided to run this double blind experiment as to whether or not we could spot one another. While I am reasonably aware of my surroundings when cycling (as a matter of mere survival), my radar rarely extends to people sitting on benches, especially when I am riding the middle white line on the boulevard. As I was further a wee bit late that day, I should have been in my office by the time Andrew sat there. A chance encounter, hence, or a super subjective inference from the author of BDA!

aftermaths of retiring significance

Posted in Books, pictures, Statistics, University life with tags , , , , , , on April 10, 2019 by xi'an


Beyond mentions in the general press of the retire significance paper, as in Retraction Watch, Bloomberg, The Guardian, Vox, and NPR, not to mention the large number of comments on Andrew’s blog, and Deborah Mayo’s tribune on a ban on free speech (!), Nature of “the week after” contained three letters from Ioannidis, calling for more stringent thresholds, Johnson, essentially if unclearly stating the same, and my friends from Amsterdam, Alexander Ly and E.J. Wagenmakers, along with Julia Haaf, getting back to the Great Old Ones, to defend the usefulness of testing versus estimation.

abandon ship [value]!!!

Posted in Books, Statistics, University life with tags , , , , , , , , , on March 22, 2019 by xi'an

The Abandon Statistical Significance paper we wrote with Blakeley B. McShane, David Gal, Andrew Gelman, and Jennifer L. Tackett has now appeared in a special issue of The American Statistician, “Statistical Inference in the 21st Century: A World Beyond p < 0.05“.  A 400 page special issue with 43 papers available on-line and open-source! Food for thought likely to be discussed further here (and elsewhere). The paper and the ideas within have been discussed quite a lot on Andrew’s blog and I will not repeat them here, simply quoting from the conclusion of the paper

In this article, we have proposed to abandon statistical significance and offered recommendations for how this can be implemented in the scientific publication process as well as in statistical decision making more broadly. We reiterate that we have no desire to “ban” p-values or other purely statistical measures. Rather, we believe that such measures should not be thresholded and that, thresholded or not, they should not take priority over the currently subordinate factors.

Which also introduced in a comment by Valentin Amrhein, Sander Greenland, and Blake McShane published in Nature today (and supported by 800+ signatures). Again discussed on Andrew’s blog.

abandon all o(p) ye who enter here

Posted in Books, Statistics, University life with tags , , , , , , on September 28, 2017 by xi'an

Today appeared on arXiv   a joint paper by Blakeley McShane, David Gal, Andrew Gelman, Jennifer Tackett, and myself, towards the abandonment of significance tests, which is a response to the 72 author paper in Nature Methods that recently made the news (and comments on the ‘Og). Some of these comments have been incorporated in the paper, along with others more on the psychology testing side. From the irrelevance of point null hypotheses to the numerous incentives for multiple comparisons, to the lack of sufficiency of the p-value itself, to the limited applicability of the uniformly most powerful prior principle…

“…each [proposal] is a purely statistical measure that fails to take a more holistic view of the evidence that includes the consideration of the traditionally neglected factors, that is, prior and related evidence, plausibility of mechanism, study design and data quality, real world costs and benefits, novelty of finding, and other factors that vary by research domain.”

One may wonder about this list of grievances and its impact on statistical practice. The paper however suggests two alternatives, one being to investigate the potential impact of (neglected) factors rather than relying on thresholds. Another one, maybe less realistic, unless it is the very same, is to report the entirety of the data associated with the experiment. This makes the life of journal editors and grant evaluators harder, possibly much harder, but it indeed suggests an holistic and continuous approach to data analysis, rather than the mascarade of binary outputs. (Not surprisingly, posting this item of news on Andrew’s blog a few hours ago generated a large amount of discussion.)

Le Monde lacks data scientists!

Posted in Books, Statistics with tags , , , , , , , on July 11, 2017 by xi'an

In a paper in Le Monde today, a journalist is quite critical of statistical analyses of voting behaviours regressed on socio-economic patterns. Warning that correlation is not causation and so on and so forth…But the analysis of the votes as presented in the article is itself quite appalling! Just judging from the above graph, where the vertical and horizontal axes are somewhat inverted (as predicting the proportion of over 65 in the population from their votes does not seem that relevant), with an incomprehensible drop in the over 65 proportion within a district between the votes for the fascist party and the other ones, both indicators of an inversion of the axes!, where the curves are apparently derived from four points [correction at the end explaining they used the whole data collection to draw the curve],  where the variability in the curves is not opposed to the overall variability in the population, where more advanced tools than mere correlation are not broached upon, and so on… They should have asked Andrew. Or YouGov!