On Aug 9, 2010, at 3:03 PM, Alain Guillet wrote: > 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.
It might be helpful to add that paired=TRUE is needed in the call to get the signed-rank test. > If there are ties, I know I prefer wilcox.exact from the exactRankTests. > (Not that much of an issue in larger sample sizes, I'd say. Even with binary data, the normal approximation works reasonably well under the usual assumptions of expected counts > 5, since the tie-adjustment for the variance is exact for the distribution of the ranks. The continuity correction doesn't quite work though. Anyways, wilcox.exact is of course a nice thing to have.) > 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! >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > -- > Alain Guillet > Statistician and Computer Scientist > > SMCS - IMMAQ - Université catholique de Louvain > Bureau c.316 > Voie du Roman Pays, 20 > B-1348 Louvain-la-Neuve > Belgium > > tel: +32 10 47 30 50 > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.