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 at gmail.com>
Sent: Thursday, March 28, 2019 12:19 AM
To: Lenth, Russell V <russell-lenth at uiowa.edu>; r-devel <r-devel at
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...?