Archive for ASA

Statistics and Health Care Fraud & Measuring Crime [ASA book reviews]

Posted in Books, Statistics with tags , , , , , , , , , , , , , , , , on May 7, 2019 by xi'an

From the recently started ASA books series on statistical reasoning in science and society (of which I already reviewed a sequel to The Lady tasting Tea), a short book, Statistics and Health Care Fraud, I read at the doctor while waiting for my appointment, with no chances of cheating! While making me realise that there is a significant amount of health care fraud in the US, of which I had never though of before (!), with possibly specific statistical features to the problem, besides the use of extreme value theory, I did not find me insight there on the techniques used to detect these frauds, besides the accumulation of Florida and Texas examples. As  such this is a very light introduction to the topic, whose intended audience of choice remains unclear to me. It is stopping short of making a case for statistics and modelling against more machine-learning options. And does not seem to mention false positives… That is, the inevitable occurrence of some doctors or hospitals being above the median costs! (A point I remember David Spiegelhalter making a long while ago, during a memorable French statistical meeting in Pau.) The book also illustrates the use of a free auditing software called Rat-stats for multistage sampling, which apparently does not go beyond selecting claims at random according to their amount. Without learning from past data. (I also wonder if the criminals can reduce the chances of being caught by using this software.)

A second book on the “same” topic!, Measuring Crime, I read, not waiting at the police station, but while flying to Venezia. As indicated by the title, this is about measuring crime, with a lot of emphasis on surveys and census and the potential measurement errors at different levels of surveying or censusing… Again very little on statistical methodology, apart from questioning the data, the mode of surveying, crossing different sources, and establishing the impact of the way questions are stated, but also little on bias and the impact of policing and preventing AIs, as discussed in Weapons of Math Destruction and in some of Kristin Lum’s papers.Except for the almost obligatory reference to Minority Report. The book also concludes on an history chapter centred at Edith Abbott setting the bases for serious crime data collection in the 1920’s.

[And the usual disclaimer applies, namely that this bicephalic review is likely to appear later in CHANCE, in my book reviews column.]

bootstrap in Nature

Posted in Statistics with tags , , , , , , , , , , on December 29, 2018 by xi'an

A news item in the latest issue of Nature I received about Brad Efron winning the “Nobel Prize of Statistics” this year. The bootstrap is certainly an invention worth the recognition, not to mention Efron’s contribution to empirical Bayes analysis,, even though I remain overall reserved about the very notion of a Nobel prize in any field… With an appropriate XXL quote, who called the bootstrap method the ‘best statistical pain reliever ever produced’!

ASA opposes USDA plan likely to undermine economic research service (ERS) work [repost]

Posted in Statistics with tags , , , , , , on September 19, 2018 by xi'an

The American Statistical Association (ASA) is actively opposing a recent United States Department of Agriculture (USDA) proposal to realign and relocate the Economic Research Service (ERS). The ASA’s concern is that moving ERS—a federal statistical agency and an internationally respected agricultural economics research institution—would undermine its work and product quality, thereby also affecting evidence-based policymaking in the USDA and food and agriculture more generally.

scientific societies start to address sexual harassement

Posted in Books, University life with tags , , , , , , on July 10, 2018 by xi'an

As ISBA releases a letter of her president to the members about the decision by the ISBA Board [taken in Edinburgh] to exclude three of its members following multiple complaints of harassment, the ASA publishes an update on the activities of the task force created to address this issue last November. And Nature reports on the report published by the US academies of Sciences, Engineering, and Medicine, which points out the limited impact of the current policies and mechanisms at play in US institutions.

“The analysis concludes that policies to fight the problem are ineffective because they are set up to protect institutions, not victims.” Nature, June 12, 2018

A common feature between the ASA and the Academy approaches is to rely on a survey of their respective members, soon to come for ASA members. Another feature of major relevance is the issue of anonymous reporting and counselling. So that victims and witnesses of harassment can trust the procedure strongly enough to report  a case without being afraid of being known to a large number of people. In my opinion, having identified individuals that represent the diversity of a scientific society such as ISBA, rather than an anonymous email account or a web form, is more likely to induce testimonies or complaints.

SDSS with friends

Posted in Statistics with tags , , , , , , , , on May 4, 2018 by xi'an

When browsing over lunch the April issue of Amstat News, I came upon this page advertising rather loudly the SDSS symposium of next month. And realised that not only it features “perhaps the most prominent statistician to have repeatedly published material written by others without attribution” (a quote from Gelman and Basbøll, 2013, in American Scientist), namely  Ed Wegman, as the guest of honor,  but also one co-author of a retracted Computational Statistics paper [still included in Wegman’s list of publications] as program chair and another co-author from the “Hockey Stick” plagiarised report as plenary speaker. A fairly friendly reunion, then, if “networking” is to be understood this way, except that this is a major conference, supported by ASA and other organisations. Rather shocking, isn’t it?! (The entry also made me realise that the three co-authors were the original editors of WIREs, before Wegman and Said withdrew in 2012.)

what is your favorite teacher?

Posted in Kids, Statistics, University life with tags , , , , , , , , on October 14, 2017 by xi'an

When Jean-Louis Foulley pointed out to me this page in the September issue of Amstat News, about nominating a favourite teacher, I told him it had to be an homonym statistician! Or a practical joke! After enquiry, it dawned on me that this completely underserved inclusion came from a former student in my undergraduate Estimation course, who was very enthusiastic about statistics and my insistence on modelling rather than mathematical validation. He may have been the only one in the class, as my students always complain about not seeing the point in slides with no mathematical result. Like earlier this week when after 90mn on introducing the bootstrap method, a student asked me what was new compared with the Glivenko-Cantelli theorem I had presented the week before… (Thanks anyway to David for his vote and his kind words!)

errors, blunders, and lies [book review]

Posted in Books, Kids, Statistics, University life with tags , , , , , , , , , on July 9, 2017 by xi'an

This new book by David Salsburg is the first one in the ASA-CRC Series on Statistical Reasoning in Science and Society. Which explains why I heard about it both from CRC Press [as a suggested material for a review in CHANCE] and from the ASA [as mass emailing]. The name of the author did not ring a bell until I saw the line about his earlier The Lady Tasting Tea book,  a best-seller in the category of “soft [meaning math- and formula-free] introduction to Statistics through picturesque characters”. Which I did not read either [but Bob Carpenter did].

The current book is of the same flavour, albeit with some maths formulas [each preceded by a lengthy apology for using maths and symbols]. The topic is the one advertised in the title, covering statistical errors and the way to take advantage of them, model mis-specification and robustness, and the detection of biases and data massaging. I read the short book in one quick go, waiting for the results of the French Legislative elections, and found no particular appeal in the litany of examples, historical entries, pitfalls, and models I feel I have already read so many times in the story-telling approach to statistics. (Naked Statistics comes to mind.)

It is not that there anything terrible with the book, which is partly based on the author’s own experience in a pharmaceutical company, but it does not seem to bring out any novelty for engaging into the study of statistics or for handling data in a more rational fashion. And I do not see which portion of the readership is targeted by the book, which is too allusive for academics and too academic for a general audience, who is not necessarily fascinated by the finer details of the history (and stories) of the field. As in The Lady Tasting Tea, the chapters constitute a collection of vignettes, rather than a coherent discourse leading to a theory or defending an overall argument. Some chapters are rather poor, like the initial chapter explaining the distinction between lies, blunders, and errors through the story of the measure of the distance from Earth to Sun by observing the transit of Venus, not that the story is uninteresting, far from it!, but I find it lacking in connecting with statistics [e.g., the meaning of a “correct” observation is never explained]. Or the chapter on the Princeton robustness study, where little is explained about the nature of the wrong distributions, which end up as specific contaminations impacting mostly the variance. And some examples are hardly convincing, like those on text analysis (Chapters 13, 14, 15), where there is little backup for using Benford’s law on such short datasets.  Big data is understood only under the focus of large p, small n, which is small data in my opinion! (Not to mention a minor crime de lèse-majesté in calling Pierre-Simon Laplace Simon-Pierre Laplace! I would also have left the Marquis de aside as this title came to him during the Bourbon Restauration, despite him having served Napoléon for his entire reign.) And, as mentioned above, the book contains apologetic mathematics, which never cease to annoy me since apologies are not needed. While the maths formulas are needed.