Archive for epidemiology

ABC [almost] in the front news

Posted in pictures, Statistics, University life with tags , , , , , , , , , , , , , , on July 7, 2014 by xi'an

cow (with TB?) on one of the ghats, Varanasi, Uttar Pradesh, Jan. 6, 2013My friend and Warwick colleague Gareth Roberts just published a paper in Nature with Ellen Brooks-Pollock and Matt Keeling from the University of Warwick on the modelling of bovine tuberculosis dynamics in Britain and on the impact of control measures. The data comes from the Cattle Tracing System and the VetNet national testing database. The mathematical model is based on a stochastic process and its six parameters are estimated by sequential ABC (SMC-ABC). The summary statistics chosen in the model are the number of infected farms per county per year and the number of reactors (cattle failing a test) per county per year.

“Therefore, we predict that control of local badger populations and hence control of environmental transmission will have a relatively limited effect on all measures of bovine TB incidence.”

This advanced modelling of a comprehensive dataset on TB in Britain quickly got into a high profile as it addresses the highly controversial (not to say plain stupid) culling of badgers (who also carry TB) advocated by the government. The study concludes that “only generic measures such as more national testing, whole herd culling or vaccination that affect all routes of transmission are effective at controlling the spread of bovine TB.” While the elimination of badgers from the English countryside would have a limited effect.  Good news for badgers! And the Badger Trust. Unsurprisingly, the study was immediately rejected by the UK farming minister! Not only does he object to the herd culling solution for economic reasons, but he “cannot accept the paper’s findings”. Maybe he does not like ABC… More seriously, the media oversimplified the findings of the study, “as usual”, with e.g. The Guardian headline of “tuberculosis threat requires mass cull of cattle”.

epidemiology in Le Monde

Posted in Books, Statistics, University life with tags , , , , , , , , , on February 19, 2012 by xi'an

Quite an interesting weekend Le Monde issue: a fourth (2 pages!) of the science folder is devoted to epidemiology… In the statistical sense. (The subtitle is actually Strengths and limitations of Statistics.) The paper does not delve into technical statistical issues but points out the logical divergence between a case-by-case study and an epidemiological study. The impression that the higher the conditioning (i.e. the more covariates), the better the explanation is a statistical fallacy some of the opponents interviewed in the paper do not grasp. (Which reminded me of Keynes seemingly going the same way.) The short paragraph written on causality and Hill’s criteria is vague enough to concur to the overall remark that causality can never been proved or disproved… The fourth examples illustrating the strengths and limitations are tobacco vs. lung cancer, a clear case except for R.A. Fisher!, mobile phones vs. brain tumors, a not yet conclusive setting, hepatitis B vaccine vs. sclerosis, lacking data (the pre-2006 records were destroyed for legal reasons), and leukemia vs. nuclear plants, with a significant [?!] correlation between the number of cases and the distance to a nuclear plant. (The paper was inspired by a report recently published by the French Académie de Médecine on epidemiology in France.) The science folder also includes a review of a recent Science paper by Wilhite and Fong on the coercive strategies used by some journals/editors to increase their impact factor, e.g., “you cite Leukemia [once in 42 references]. Consequently, we kindly ask you to add references of articles published in Leukemia to your present article”.

the cult of significance

Posted in Books, Statistics, University life with tags , , , , , , , , , , , , , on October 18, 2011 by xi'an

Statistical significance is not a scientific test. It is a philosophical, qualitative test. It asks “whether”. Existence, the question of whether, is interesting. But it is not scientific.” S. Ziliak and D. McCloskey, p.5

The book, written by economists Stephen Ziliak and Deirdre McCloskey, has a theme bound to attract Bayesians and all those puzzled by the absolute and automatised faith in significance tests. The main argument of the authors is indeed that an overwhelming majority of papers stop at rejecting variables (“coefficients”) on the sole and unsupported basis of non-significance at the 5% level. Hence the subtitle “How the standard error costs us jobs, justice, and lives“… This is an argument I completely agree with, however, the aggressive style of the book truly put me off! As with Error and Inference, which also addresses a non-Bayesian issue, I could have let the matter go, however I feel the book may in the end be counter-productive and thus endeavour to explain why through this review.  (I wrote the following review in batches, before and during my trip to Dublin, so the going is rather broken, I am afraid…) Continue reading

Numbers rule your world

Posted in Books, Statistics with tags , , , , , , , , , , , on February 22, 2010 by xi'an

Andrew Gelman gave me a copy of the recent book Numbers rule your world by Kaiser Fung, along with the comment that it was a nice book but not for us. I spend my “lazy Sunday” morning reading the book at the breakfast table and agree with Andrew on his assessment. (waiting for the  incoming blog review!). Numbers rule your world is unlikely to bring enlightment to professional or academic statisticians, but it provides a nice and soft introduction to the use of statistics in everyday’s life, to the point I would encourage my second and third year students to read it. It covers a few topics that are central to Statistics via ten newspaper-ised stories that make for a very light read, but nonetheless make the point. The themes in Numbers rule your world are

  • variability matters more than average, as illustrated by queuing phenomena;
  • correlation is not causation, but is often good enough to uncover patterns, as illustrated by epidemiology and credit scoring;
  • Simpson’s paradox explains for apparent bias in group differences, as illustrated by SAT score differences between black students and white students;
  • false positives and false negatives have different impacts on the error (here comes Bayes theorem!), depending on population sizes and settings, as illustrated by the (great!) case of cheating athletes and polygraph tests (with a reference to Steve Fienberg‘s work);
  • extreme events may exhibit causes, or not, as illustrated by a cheating lottery case (involving Jeff Rosenthal as the expert, not the cheater!) and a series of air crashes.

The overall tone of Numbers rule your world is pleasant and engaging, at the other end of the stylistic spectrum from Taleb’s Black Swan. Fung’s point is obviously the opposite of Taleb‘s: he is showing the reader how well statistical modelling can explain for apparently paradoxical behaviour. Fung is also adopting a very neutral tone, again a major change from Taleb, maybe being even too positive (no the only mention is made of the current housing crisis in the pages Numbers rule your world dedicates to credit scoring comes in the conclusion, pp. 176-7). Now, in terms of novelty, I cannot judge of the amount of innovation when compared with (numerous) other popular science books on the topic. For instance, I think Jeff Rosenthal’s Struck by Lightning brings a rather deeper perspective, but maybe thus restricts the readership further…