On Wed, 28 Oct 2009, David Croll wrote:
Dear Achim,
let me thank you for this assurance!
The sample size is too large (~4000 observations per group) to solve this
problem exactly. The error message could maybe be improved, but the message
is clear: This is too large to deal with.
However, this is not a problem. With several thousand observations,
standard normal approximations should work sufficiently well. And if you
don't believe it, then you can look at approximate solutions that draw a
sufficiently large number of permutations. Both is easily available when
using wilcox_test() in "coin" as the startup message of "exactRankTests"
suggests.
But in my dataset there are many, many tied ranks between group_1 and group_2
and the other ones. I wanted to use the exact procedure because I read the
approximate solution would not give me exact p values in case of tied
ranks...
Well, normal asymptotics will work anyway.
Am I paranoid, or am I in search of an exactness statistics cannot
deliver?
Paranoid. ;-) With your sample size all solutions should be sufficiently
close to exact.
Well, then I'll try permutation tests, and thank you again!
wilcox.exact() is a permutation test (as is wilcox.test if there are no
ties). However, not all permutations have to be computed explicitly which
is why it is also feasible for moderately sized samples. For large samples
as yours, the computational burden is too large even for wilcox.exact().
The usual solution is to not look at all permutations but at a large
number of them where you can make the approximation as precise as you want
by increasing the number of permutations. And I'm fairly certain (but
haven't tried) that the result of the approximate permutation test will be
almost the same as the asymptotic permutation test.
hth,
Z
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