I'm trying to analyze data that violates the assumptions of an ANOVA (homogeneity of variances), thus I think I have to conduct a non-parametric test. My study follows a factorial completely randomized design: 3 sources 4 treatments 4 replicates per treatment*source combination (replicates are equal in size)
Dependent variable is seed germination.
The Kruskal-Wallase test was suggested to me, but is there a way to do it and test for both source, treatment, and source*treatment interaction? Furthermore, can I draw pair-wise comparisons between source*treatment combinations much like Tukeys LSD would do?
Could I use PROC GLIMMIX in SAS instead? If so, what are the assumptions that need to be met for that model and how do I make sure that I'm meeting them?