Monday, September 18, 2017

More D&A and FvB.

By chance I happened to notice another paper with an interesting title appearing in Climatic Change on the very same day as the recent Mann et al paper: Is the choice of statistical paradigm critical in extreme event attribution studies? While my noticing it was fortuitous, the publication date was no coincidence, as it was clearly intended as a "comment on" in all but name. I am not particularly impressed by such shenanigans. I know that Nature often publishes a simultaneous commentary along with the article itself, but these are generally along the lines of a sycophantic laudation extolling the virtues of the new work. The climatic change version seems to be designed to invite a critical comment which does not provide the authors under attack any right to reply. Jules and I were previously supposed to be a victim of this behaviour when we published this paper. However the commentary never got written, so in the end we suffered nothing more than a lengthy delay to final publication.

Anyway, back to the commentary. Is the choice of statistical paradigm critical? I can't really be bothered discussing it in any detail. The arguments have been hashed out before (including on this blog, e.g. here). The authors provide a rather waffly defence of frequentist approaches without really providing any credible support IMO, based on little more than some rather silly straw men. Of course a badly-chosen prior can give poor results, but so can an error in your computer program or a typo in your manuscript, and no-one argues that it's better to just take a guess instead of doing a calculation and writing down the answer. Well, almost no-one.


3 comments:

Everett F Sargent said...

Well, I found it a week ago and made three comments at ATTP ...
https://andthentheresphysics.wordpress.com/2017/09/09/prior-knowledge/#comment-102922
https://andthentheresphysics.wordpress.com/2017/09/09/prior-knowledge/#comment-102923
https://andthentheresphysics.wordpress.com/2017/09/09/prior-knowledge/#comment-102947

MLO17 Meehl (2007) reference is (IMHO) bogus. I'm much more interested in a one sided distro (say Rice) and p values biased by only a few percent (e. g. that one would find in say GMST anomaly slope). The transition, so far, isn't step-like but gradual.

I'm here to learn the errors of my ways though.

David B Benson said...

Learn to use the Bayes factor to compare hypotheses. No priors required.

James Annan said...

A valid point but that comparison doesn't necessarily answer the question posed...