Thomas Farrar wrote:
Hi all,
The Kruskal-Wallis test is a generalization of the two-sample Mann-Whitney
test to *k* samples. That being the case, the Kruskal-Wallis test with *k*=2
should give an identical p-value to the Mann-Whitney test, should it not?
x1<-c(1:5)
x2<-c(6,8,9,11)
a<-wilcox.test(x1,x2,paired=FALSE)
b<-kruskal.test(list(x1,x2),paired=FALSE)
a$p.value
[1] 0.01587302
b$p.value
[1] 0.01430588
The p-values are slightly different (note that there are no ties in the
data, so computed p-values should be exact).
Can anyone explain the discrepancy? It's been awhile since I studied
nonparametric stats and this one has me scratching my head.
Many thanks!
Tom
The continuity correction? It is true by default for wilcox.test and is
not apparent in the help for kruskal.test.
David Scott
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David Scott Department of Statistics
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Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055
Email: d.sc...@auckland.ac.nz, Fax: +64 9 373 7018
Director of Consulting, Department of Statistics
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