> qwilcox(p,5,5)
p: 0.025 0.975 -------------------- R> 3 22 S> 18 37
I originally wanted to ask a questions, but then I found the answer. Given the confusion I run into, I wonder if this experience is worth reporting.
The S-Plus quantiles are almost correct (they are the limits of the region of acceptance, rather than the quantiles). The description in the R help file
Distribution of the Wilcoxon Rank Sum Statistic
suggests that R:qwilcox also gives quantiles for the rank sum (which the Wilcoxon rank sum test is based on). In fact, however, it gives quantiles for the u-statistic (which the Mann-Whitney test is based upon). While the tests are logically equivalent, the particular test statistics
- sum(Xi>c(X,Y)) rank sum (Wilcoxon) - sum(Xi>c( Y)) u statistic (Mann-Whitney)
are different (apologies for the non-standard notation). Since "wilcox.test" relates to the rank sums in both R and S, as does qwilcox in S, the name 'qwilcox' in R may be misleading. How about renaming it to 'qmannwhitney' instead and adding 'qwilcoxon' for a function that corresponds to S:qwilcox?
> x1 <- c(1,2,3, 5,6 ) > x2 <- c( 4, 7,8,9,10) > sum(x1) [1] 17 > sum(x2) [1] 38
R> wilcox.test(x1,x2,alternative="two.sided") Wilcoxon rank sum test: p-value = 0.03175
R> wilcox.exact(x1,x2,alternative="two.sided") Exact Wilcoxon rank sum test: p-value = 0.03175
S> wilcox.test(x1,x2,alternative="two.sided") Exact Wilcoxon rank-sum test: p-value = 0.0317
> x1 <- c(1,2, 4,5,6 ) > x2 <- c( 3, 7,8,9,10) > sum(x1) [1] 18 > sum(x2) [1] 37
R> wilcox.test(x1,x2,alternative="two.sided") Wilcoxon rank sum test: p-value = 0.05556
R> wilcox.exact(x1,x2,alternative="two.sided") Exact Wilcoxon rank sum test: p-value = 0.05556
S> wilcox.test(x1,x2,alternative="two.sided") Exact Wilcoxon rank sum test: p-value = 0.0556
Knut M. Wittkowski, PhD,DSc ------------------------------------------ The Rockefeller University, GCRC 1230 York Ave #121B, Box 322, NY,NY 10021 +1(212)327-7175, +1(212)327-8450 (Fax) [EMAIL PROTECTED] http://www.rucares.org/statist/
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