Hi,
Look at the output of the test made in R and you can see it is a
Wilcoxon rank sum test and not a Wilcoxon signed rank test.
If there are ties, I know I prefer wilcox.exact from the exactRankTests.
Alain
On 09-Aug-10 12:43, Capasia wrote:
This is my first post to the mailing list and I guess it's a pretty stupid
question but I can't figure it out. I hope this is the right forum for these
kind of questions.
Before I started using R I was using STATA to run a Wilcoxon signed-rank
test on two variables. See data below:
https://spreadsheets.google.com/pub?key=0ApodAA2GAEP_dDZkdzZHSFBqX1JHOWJBX1dMQUZCVkE&hl=en&output=html<%20%20https://spreadsheets.google.com/pub?key=0ApodAA2GAEP_dDZkdzZHSFBqX1JHOWJBX1dMQUZCVkE&hl=en&output=html>
STATA Output:
. signrank x=y
Wilcoxon signed-rank test
sign | obs sum ranks expected
-------------+---------------------------------
positive | 41 3101 2330.5
negative | 18 1560 2330.5
zero | 49 1225 1225
-------------+---------------------------------
all | 108 5886 5886
unadjusted variance 106438.50
adjustment for ties -282.38
adjustment for zeros -10106.25
----------
adjusted variance 96049.88
Ho: transfer_2_a = transfer_2_b
z = 2.486
Prob> |z| = *0.0129*
When running a Wilcoxon signed-rank test
wilcox.test(datablatt$x, datablatt$y)
Wilcoxon rank sum test with continuity correction
data: datablatt$x and datablatt$y
W = 7059.5, p-value = *0.09197*
alternative hypothesis: true location shift is not equal to 0
As you can see the p Values are different (one with H0 rejection and the
other one not). I tested whether it could be that the STATA one isn't paired
but this doesn't seem to be the problem.
I'm dumbfound what could lead to such a difference. I couldn't find any
seetings I have missed but I somehow I guess I'm using the function in the
wrong way...
Any ideas?
Thanks a lot in advance!
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Alain Guillet
Statistician and Computer Scientist
SMCS - IMMAQ - Université catholique de Louvain
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