[Rd] [External] re: default for 'signif.stars'

[Lenth, Russell V]

Abs,

There are definitely problems with the editorial, but I think "most mega-ultra-super-biased" is an overreaction. It appears that you have overlooked some of the points made there, and the fact that it does not pretend to be an exhaustive list of alternative methods. The editorial attempts to digest what is in 43 articles in that special issue. Some of those articles do promote Bayesian methods – not a surprise – and some advocate using P values but without ascribing magical properties to P < 0.05. My own emmeans package does present P values (sans stars, or emojis either) in a lot of contexts.

More to the point, the criticisms you offer have to do with later sections of the editorial – not the initial part, which is largely a repeat of an earlier ASA statement on interpretation of P values with the added recommendation that people should never say "statistically significant." It is that initial part that I think does describe a consensus of a large and growing proportion of statisticians and other scientists that placing undue emphasis on "statistical significance" is a bad thing. Emphasizing P values by adding stars encourages that kind of misdirected emphasis.

It seems fairly harmless to change the default for "show.signif.stars" to FALSE. However, I do recognize that no change to R's defaults should be taken lightly or done without careful consideration. I only ask that such careful consideration take place, and hope in fact that a plan can be made to phase-in such a change. 

Thanks,

Russ

Russell V. Lenth  -  Professor Emeritus
Department of Statistics and Actuarial Science   
The University of Iowa  -  Iowa City, IA 52242  USA   
Voice (319)335-0712 (Dept. office)  -  FAX (319)335-3017



From: Abs Spurdle <spurdle.a using gmail.com> 
Sent: Thursday, March 28, 2019 12:19 AM
To: Lenth, Russell V <russell-lenth using uiowa.edu>; r-devel <r-devel using r-project.org>
Subject: [External] re: [Rd] default for 'signif.stars'

I read through the editorial.
This is the one of the most mega-ultra-super-biased articles I've ever read.

e.g.
The authors encourage Baysian methods, and literally encourage subjective approaches.
However, there's only one reference to robust methods and one reference to nonparametric methods, both of which are labelled as purely exploratory methods, which I regard as extremely offensive.
And there don't appear to be any references to semiparameric methods, or machine learning.

Surprisingly, they encourage multiple testing, however, don't mention the multiple comparison problem.
Something I can't understand at all.

So, maybe we should replace signif.stars with emoji...?