[R] Test for multiple contrasts?
lhomer at teleport.com
Sat Feb 10 03:07:49 CET 2001
The p.adjust methods "work" for correlated tests in the sense that the
inequalities one would normally write should be correct. There is no option
for introducing correlations into my version of p.adjust and so no way of
adjusting p.adjust output when there are correlations among the p values. In
these cases the adjustments will often be excessive.
----- Original Message -----
From: Peter Dalgaard BSA <p.dalgaard at biostat.ku.dk>
To: <pflugshaupt at geobot.umnw.ethz.ch>
Cc: <r-help at stat.math.ethz.ch>
Sent: Thursday, February 08, 2001 7:27 AM
Subject: Re: [R] Test for multiple contrasts?
> Kaspar Pflugshaupt <pflugshaupt at cirsium.ethz.ch> writes:
> > Now, I'd like to test which of my contrasts are significantly different
> > zero. I assume that the p values given by the summary are not corrected
> > multiple testing. Thus, I might correct them with p.adjust(). But since
> > contrasts are not independent, I'm not sure if the adjustment methods
> > work here.
> > On the other hand, I've come across a procedure called "Scheffe's
> > comparisons" (or S test), which is said to be appropriate for multiple
> > contrasts like these. Before I try to implement it: Has anybody already
> > that, or are there good reasons not to use it?
> The p.adjust methods do work for correlated tests, at least the Holm
> and Bonferroni tests where I can understand the theory. The Hochberg
> test has some amount of handwaving associated with it, but it too is
> intended to be applied to testing contrasts.
> Scheffe also works with correlated tests. It is more conservative than
> the other tests because it protects against multiple testing on any
> number of linear contrasts by projecting the (F-based) multivariate
> confidence region onto the direction given by the contrast. This
> argues both for and against its use...
> > BTW, I tried to extract the SEs of the contrasts by se.contrast(), but
> > would not work for survival models. Would they be the same that appear
> > summary above?
> se.contrast works for aov models only. You probably need to massage
> the covariance matrix for the estimates.
> O__ ---- Peter Dalgaard Blegdamsvej 3
> c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
> (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
> ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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