generating a paired t-test with multiple levels of a factor
Rolf Turner wrote:
On 28/03/2008, at 11:14 AM, Peter Dalgaard wrote:
Michael A. Miller wrote:
"James" == James Root <jcroot at gmail.com> writes:
Is there a way to run all paired t-tests where a paired t-test is run for every possible combination?
Sounds like pairwise.t.test is the sort of thing you are looking for...
Yes, except that it was designed for independent samples t-tests, so you need to be careful about not mixing up the pairs. This appears to do the trick:
pairwise.t.test(a,col(a),paired=T,pool=F,p.adj="none")
Pairwise comparisons using t tests with non-pooled SD
<snip>
I would very strongly call this a bug in pairwise.t.test. One should
*not* have to specify pool=FALSE if one is doing a paired t-test. For
a paired t-test there is actually only *one* sample (the sample of
pairwise
differences) and hence only one standard deviation, and hence nothing
to pool.
It's not a bug that something works strangely outside its intended domain...
The documentation says:
Description:
Calculate pairwise comparisons between group levels with
corrections for multiple testing
which does not imply that paired tests should work. Had that been the
intention, it would have been documented (and presumably, more thought
would have gone into figuring out whether it makes sense to pool the SD,
and if so, how to do it.)
My reading of the code is that if pool.sd is TRUE (the default) then the
pairwise.t.test function does two-independent-sample t-tests willy-nilly,
and ignores the ``paired=TRUE'' argument. (It doesn't call upon t.test()
which is the only bit which considers the ``paired'' argument.)
This is a dangerous trap, and should be fixed. (Which is not hard.)
cheers,
Rolf
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O__ ---- Peter Dalgaard ?ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907