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
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