This is a mixed question, between theory and practice. I have a dataset with a continous variable grouped by a 33 levels factor. After having log-tranformed my original data I can assume the normality of my data but I have two strong departures from the basic assumptions for anova and t tests: *unbalanced data* (some groups contain ten samples, others hundreds) and *non homogenity of variances* (tested with a kruscal test just for a qualitative assessment). Is it possible, and how, to make multiple comparisons when these conditions are met? In past anaylises I've simply used the pairwise.t.test function to do multiple t-test, but know I have to consider the above situation...
Thanks a lot, giovanni ______________________________________________ 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.
