Where did you get the idea that the location estimate in a 2-sample
Wilcoxon test is the difference in medians? (It is a common
misconception, but not I believe to be found in R. The estimate is
the median of differences, not the difference of medians: and the test
is not of a difference of population medians either, unless the two
populations differ only in location.)
On Sun, 30 Jan 2011, Graham Smith wrote:
I am sure I am opening myself up to looking stupid, but I have two samples
with medians of 613.5 and 189 (difference in location of 424 compared to
the difference suggested from the wilcoxon of 291.5)
wilcox.test(pipwtCount,pipwdCount, conf.int=TRUE, na.rm=TRUE)
Wilcoxon rank sum test
data: pipwtCount and pipwdCount
W = 822, p-value = 0.01227
alternative hypothesis: true location shift is not equal to 0
95 percent confidence interval:
58 639
sample estimates:
difference in location
291.5
The data is here
pipwtCount
[1] 532 298 215 1588 38 180 284 376 5349 1024 650 605 1307 6147
21
[16] 453 23 1983 1048 464 2183 1028 1361 163 175 5944 569 622 793
70
[31] 67 1188 248 3010 19 2179 1339 408 113 739 2615 4619
pipwdCount
[1] 89 384 12 703 2 138 189 383 314 482 96 907 90 1193
154
[16] 305 61 414 4764 1066 121 143 102 174 44 2896 NA 1103 161
199
median(pipwtCount)
[1] 613.5
median(pipwdCount,na.rm=T)
[1] 189
613.5-189
[1] 424.5
I would appreciate if someone could point out the obvious to me, and explain
why there is such a large discrepancy in the differences in location.
Many thanks,
Graham
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Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
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