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...