Thank you for your answer. The p.adj argument in the kruskal()-function doesn't seem to change anything... Not even the "bonferroni"-method although it is described as the most conservative one (multiplying all p-values with the number of comparisons). I suppose the kruskal()-function is not working properly... On the other hand I doubt the method behind the kruskalmc()-function as this function doesn't even turn out to detect significant differences between the grouping variable (which is obviously a severe error). Do you think it is justifiable to use the kruskal()-function without p-adjustment, i.e. doing only pairwise tests like you can do with the kruskal.test()-function although I obviously want to do multiple comparisons?
kruskal(x[,1],x[,2],p.adj="bonferroni") #Yields exactely the same results. #Groups, Treatments and mean of the ranks #a 11 304.4 #ab 9 296 #ab 7 286.6 #ab 8 278.2 #ab 10 268.7 #ab 2 250.6 #ab 6 242.9 #ab 1 242.1 #ab 3 239.4 #ab 5 228.8 #b 4 219.5 kruskalmc(x[,2],x[,2]) #Multiple comparison test after Kruskal-Wallis #p.value: 0.05 #Comparisons # obs.dif critical.dif difference #[......] #6-9 54.0 162.02688 FALSE #6-10 69.5 159.04584 FALSE #6-11 94.5 133.02196 FALSE #7-8 18.0 160.00778 FALSE #7-9 35.0 169.78370 FALSE #7-10 50.5 166.94123 FALSE #7-11 75.5 142.36796 FALSE #8-9 17.0 165.54197 FALSE #8-10 32.5 162.62538 FALSE #8-11 57.5 137.28174 FALSE #9-10 15.5 172.25281 FALSE #9-11 40.5 148.56074 FALSE #10-11 25.0 145.30369 FALSE -- View this message in context: http://r.789695.n4.nabble.com/Multiple-Comparisons-Kruskal-Wallis-Test-kruskal-agricolae-and-kruskalmc-pgirmess-don-t-yield-the-sa-tp4639004p4639027.html Sent from the R help mailing list archive at Nabble.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.
