[Rd] default for 'signif.stars'
men@ur@t|on|@t @end|ng |rom gm@||@com
Thu Mar 28 21:03:43 CET 2019
I take your point - but I'd argue that significance stars are a clumsy
solution to the very real problem that you outline, and their inclusion as
a default sends a signal about their appropriateness that I would prefer R
not to endorse.
My preference (to the extent that it matters) would be to see the
significance stars be an option but not a default one, and the addition of
different functionality to handle the many-predictor problem, perhaps a new
summary that more efficiently provides more useful information.
If we were to invent lm() now, how would we solve the problem of big P? I
don't think we would use stars.
On Thu, 28 Mar 2019 at 20:19, Martin Maechler <maechler using stat.math.ethz.ch>
> >>>>> Lenth, Russell V
> >>>>> on Wed, 27 Mar 2019 00:06:08 +0000 writes:
> > Dear R-Devel, As I am sure many of you know, a special
> > issue of The American Statistician just came out, and its
> > theme is the [mis]use of P values and the many common ways
> > in which they are abused. The lead editorial in that issue
> > mentions the 2014 ASA guidelines on P values, and goes one
> > step further, by now recommending that the words
> > "statistically significant" and related simplistic
> > interpretations no longer be used. There is much
> > discussion of the problems with drawing "bright lines"
> > concerning P values.
> > This is the position of a US society, but my sense is that
> > the statistical community worldwide is pretty much on the
> > same page.
> > Meanwhile, functions such as 'print.summary.lm' and
> > 'print.anova' have an argument 'signif.stars' that really
> > does involve drawing bright lines when it is set to
> > TRUE. And the default setting for the "show.signif.stars"
> > option is TRUE. Isn't it time to at least make
> > "show.signif.stars" default to FALSE? And, indeed, to
> > consider deprecating those 'signif.stars' options
> > altogether?
> Dear Russ,
> Abs has already given good reasons why this article may well be
> considered problematic.
> However, I think you and (many but not all) others who've raised
> this issue before you, slightly miss the following point.
> If p-values are misleading they should not be shown (and hence
> the signif.stars neither.
> That has been the approach adopted e.g., in the lme4 package
> *AND* has been an approach originally used in S and I think
> parts of R as well, in more places than now, notably, e.g., for
> print( summary(<glm>) ).
> Fact is that users will write wrappers and their own packages
> just to get to p values, even in very doubtful cases...
> But anyway that (p values or not) is a different discussion
> which has some value.
> You however focus on the "significance stars". I've argued for
> years why they are useful, as they are just a simple
> visualization of p values, and saving a lot of human time when
> there are many (fixed) effects looked at simultaneously.
> Why should users have to visually scan 20 or 50 numbers? In
> modern Data analysis they should never have to but rather look
> at a visualization of those numbers. ... and that's what
> significance stars are, not more, nor less.
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