Archive for Monsanto

Valen in Le Monde

Posted in Books, Statistics, University life with tags , , , , , , , , , , on November 21, 2013 by xi'an

Valen Johnson made the headline in Le Monde, last week. (More precisely, to the scientific blog Passeur de Sciences. Thanks, Julien, for the pointer!) With the alarming title of “(A study questions one major tool of the scientific approach). The reason for this French fame is Valen’s recent paper in PNAS, Revised standards for statistical evidence, where he puts forward his uniformly most powerful Bayesian tests (recently discussed on the ‘Og) to argue against the standard 0.05 significance level and in favour of “the 0.005 or 0.001 level of significance.”

“…many statisticians have noted that P values of 0.05 may correspond to Bayes factors that only favor the alternative hypothesis by odds of 3 or 4–1…” V. Johnson, PNAS

While I do plan to discuss the PNAS paper later (and possibly write a comment letter to PNAS with Andrew), I find interesting the way it made the headlines within days of its (early edition) publication: the argument suggesting to replace .05 with .001 to increase the proportion of reproducible studies is both simple and convincing for a scientific journalist. If only the issue with p-values and statistical testing could be that simple… For instance, the above quote from Valen is reproduced as “an [alternative] hypothesis that stands right below the significance level has in truth only 3 to 5 chances to 1 to be true”, the “truth” popping out of nowhere. (If you read French, the 300+ comments on the blog are also worth their weight in jellybeans…)

Statistique dans Le Monde

Posted in University life with tags , , , , , , , , , , , on November 5, 2012 by xi'an

Again, some relevant entries in the weekend edition of Le Monde: a paper on Nate Silver and his FivThirtyEight blog, with a short description of his statistical approach, namely to pool all existing polls in a sort of meta-analysis. Not going as far as mentioning LOESS or nearest neighbour regression techniques. [Even less Bayesian!] For this, the FAQ of FivThirtyEight is much more explicit:

Firstly, we assign each poll a weighting based on that pollster’s historical track record, the poll’s sample size, and the recentness of the poll. More reliable polls are weighted more heavily in our averages.

Secondly, we include a regression estimate based on the demographics in each state among our ‘polls’, which helps to account for outlier polls and to keep the polling in its proper context.

Thirdly, we use an inferential process to compute a rolling trendline that allows us to adjust results in states that have not been polled recently and make them ‘current’.

Fourthly, we simulate the election 10,000 times for each site update in order to provide a probabilistic assessment of electoral outcomes based on a historical analysis of polling data since 1952. The simulation further accounts for the fact that similar states are likely to move together, e.g. future polling movement in states like Michigan and Ohio, or North and South Carolina, is likely to be in the same direction

The second paper is a tribune written by Marc Lavielle, senior researcher at INRIA Saclay, on the (French) debate surrounding the recent publication of a study by Séralini et al. on the toxicity of the genetically modified NK603 (Monsanto) corn. Part of the controversy stems form the fact that this paper was distributed to the media prior to its publication with a confidentiality contract that prevented the media to consult other experts (but not from publishing nonsensical definitive headlines). Another part of the controversy comes from the publication by six of the French Académies (namely, Science, Agriculture, Medicine, Pharmacy, Technologies, and Veterinary) of a statement concluding to the lack of reliability of the Food and Chemical Toxicology paper by Séralini et al., followed by another tribune written by Paul Deheuvels, professor of statistics at Université Pierre et Marie Curie and member of the Académie des Sciences, tribune in which he disagrees with the opinion expressed in this statement and legitimately complains not being consulted while being the sole statistician member of the Academy of Sciences. (This debate was also reported in the recent October recap of CNRS Images des Mathématiques.)