I have an experiment producing results (dependent variables) that don't pass tests of normality, thus I am testing hypotheses using non-parametric tests. My DVs are continuous, while my factors (independent variables) are ordinal or nominal. I've been using the Kruskal-Wallis test and Friedman test (using Matlab). Most of the time I am only interested I testing 2 IVs for significant effects, though sometimes I test 3.
I would like to know whether there are any significant interaction effects on the DV between my IVs. Normally I'd use a 2-way ANOVA to do this, however that's not appropriate given the non-normal distributions. I don't wish to use transformation of my IVs, nor go ahead with ANOVA despite non-normality.
How can I find which interaction effects are significant?
What non-parametric test could I use?
Hope someone can help.