Robert, you can do the corresponding paired comparisons using wilcox.test. As far as I know, there is no such general correction as Tukey's HSD for the Kruskal-Wallis-Test. However, if you have indeed only 3 groups (resulting in 3 paired comparisons), the intersection-union principle and the theory of closed test procedures should allow you to do these test without further correction, given the global test was statistically significant.
HTH, Michael > -----Original Message----- > From: r-help-boun...@r-project.org > [mailto:r-help-boun...@r-project.org] On Behalf Of Robert Kalicki > Sent: Mittwoch, 14. Oktober 2009 09:17 > To: r-help@r-project.org > Subject: [R] post-hoc test with kruskal.test() > > Dear R users, > > I would like to know if there is a way in R to execute a > post-hoc test (factor levels comparison, like Tukey for > ANOVA) of a non-parametric analysis of variance with > kruskal.test() function. I am comparing three different > groups. The preliminary analysis using the > kruskal-wallis-test show significance, but I still don't know > the relationship and the significance level between each group? > > > > Do you have any suggestion? > > > > Many thanks in advance! > > > > Robert > > > > > > ___________________________________________ > Robert M. Kalicki, MD > > Postdoctoral Fellow > > Department of Nephrology and Hypertension > > Inselspital > > University of Bern > > Switzerland > > > > Address: > > Klinik und Poliklinik für Nephrologie und Hypertonie > > KiKl G6 > > Freiburgstrasse 15 > > CH-3010 Inselspital Bern > > > > Tel +41(0)31 632 96 63 > > Fax +41(0)31 632 14 58 > > > > > [[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.