Hello. We have some questions concerning the statistical analysis of a dataset. We aim to compare the sample means of more than 2 independent samples; the sample sizes are unbalanced. The requirements of normality distribution and variance homogeneity were not met even after transforming the data. Thus we applied a nonparametric test: the Kruskal-Wallis-test (H-Test). The null hypothesis was rejected. Now we try to find a suitable posthoc-test in order to find out which sample means actually are statistically different.
1. We think that the Behrens-Fisher-test and multiple steel test are not applicable, because they assume normality distribution as far as we know. Is that right? 2. Statistical literature suggested to do a Nemenyi-test as posthoc-test. But this test in general requires balanced sample sizes; so we need a special type of this test. Is it possible to do such a test in R? 3. We could also test all the samples against each other with a nonparamatric Mann-Whitney-U-test and correct for the multiple comparisons (m = 11) according to Bonferroni. Is this testing method allowed? We would be very grateful, if anyone could help us. Thank you very much! Christine Hellmann and Rabea Sutter -- View this message in context: http://www.nabble.com/Kruskal-Wallis-test%3A-Posthoc-test--tp22794025p22794025.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.
