[R-sig-ME] Fwd: same old question - lme4 and p-values
reinhold.kliegl at gmail.com
Sat Apr 5 13:52:42 CEST 2008
"If you mean to replace them with confidence intervals, I have no
problem with that."
That's what I mean or, perhaps, credibility intervals. Of course, I do
not want to do away with statistics but, in perspective, hope for an
increase in sophisticated application.
On Sat, Apr 5, 2008 at 1:21 PM, Jonathan Baron <baron at psych.upenn.edu> wrote:
> On 04/05/08 12:10, Reinhold Kliegl wrote:
> > Here is a section that worked in Kliegl, Risse, & Laubrock (2007, J
> > Exp Psychol:Human Perception and Performance, 33, 1250-1251).
> This is extremely helpful.
> > In perspective, I think the p-value problem will
> > simply go away.
> I'm not sure what you mean here. If you mean to replace them with
> confidence intervals, I have no problem with that. But, as a journal
> editor, I am afraid that I will continue to insist on some sort of
> evidence that effects are real. This can be done in many ways. But
> too many authors submit articles in which the claimed effects can
> result from random variation, either in subjects ("participants*") or
> items, and they don't correctly reject such alternative explanations
> of a difference in means.
> I have noticed a kind of split among those who comment on this issue.
> On the one side are those who are familiar with fields such as
> epidemiology or economics (excluding experimental economics), where
> the claim is often made that "the null hypothesis is always false
> anyway, so why bother rejecting it?" These are the ones interested in
> effect sizes, variance accounted for, etc. They are correct for this
> kind of research, but there are other kinds of research.
> On the other side, are those from (e.g.) experimental psychology,
> where the name of the game is to design experiments that are so well
> controlled that the null hypothesis will be true if the effect of
> interest is absent. As a member of this group, when I read people
> from the first group, I find it very discouraging. It is almost as if
> they are saying that what I work so hard to try to do is impossible.
> To get a little specific, although I found Gelman and Hill's book very
> helpful on many points (and it does not deny the existence of people
> like me), it is written largely for members of the first group. By
> contrast, Baayen's book is written for people like me, as is the
> Baayen, Davidson, and Bates article, "Mixed effects modeling with
> crossed random effects for subjects and items."
> I'm afraid we do need significance tests, or confidence intervals, or
> * On "participants" vs. "subjects" see:
> Jonathan Baron, Professor of Psychology, University of Pennsylvania
> Home page: http://www.sas.upenn.edu/~baron
> Editor: Judgment and Decision Making (http://journal.sjdm.org)
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