[R] LSD, HSD,...
john.maindonald at anu.edu.au
Tue Jul 17 01:49:53 CEST 2007
<follow-on rant> Stepwise regression variable selection
methods make multiple post hoc comparisons. The
number of comparisons may be very large, vastly more
than the half-dozen post-hoc comparisons that are
common in an experimental design context.
There is a disconnect here. The multiple testing issue is
noted in pretty much every discussion of analysis of
experimental data, but not commonly mentioned (at least
in older texts) in discussions of stepwise regression, best
subsets and related regression approaches. One reason
for this silence may be that there is no ready HSD-like fix.
The SEs and t-statistics that lm() gives for the finally
selected model can be grossly optimistic. Running the
analysis with the same model matrix, but with y-values
that are noise, can give a useful wake-up call.
John Maindonald email: john.maindonald at anu.edu.au
phone : +61 2 (6125)3473 fax : +61 2(6125)5549
Centre for Mathematics & Its Applications, Room 1194,
John Dedman Mathematical Sciences Building (Building 27)
Australian National University, Canberra ACT 0200.
On 16 Jul 2007, at 8:00 PM, Simon Blomberg wrote:
> If you have a priori planned comparisons, you can just test those
> linear contrasts, with no need to correct for multiple testing. If you
> do not, and you are relying on looking at the data and analysis to
> you which treatment means to compare, and you are considering several
> tests, then you should consider correcting for multiple testing. There
> is a large literature on the properties of the various tests.
> (Tukey HSD
> usually works pretty well for me.)
> <rant> Why do people design experiments with a priori hypotheses in
> mind, yet test them using post hoc comparison procedures? It's as if
> they are afraid to admit that they had hypotheses to begin with! Far
> better to test what you had planned to test using the more powerful
> methods for planned comparisons, and leave it at that.
> On Mon, 2007-07-16 at 09:52 +0200, Adrian J. Montero Calvo wrote:
>> I'm designing a experiment in order to compare the growing of
>> several clones of a tree specie. It will be a complete randomized
>> design. How can I decide what model of mean comparision to choose?
>> HSD,TukeyHSD, Duncan,...? Thanks in advance
>> R-help at stat.math.ethz.ch mailing list
>> PLEASE do read the posting guide http://www.R-project.org/posting-
>> and provide commented, minimal, self-contained, reproducible code.
> Simon Blomberg, BSc (Hons), PhD, MAppStat.
> Lecturer and Consultant Statistician
> Faculty of Biological and Chemical Sciences
> The University of Queensland
> St. Lucia Queensland 4072
> Room 320 Goddard Building (8)
> T: +61 7 3365 2506
> email: S.Blomberg1_at_uq.edu.au
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