preceded by has_specified_input has_specified_output achieves_planned_objective multiple testing correction objective data transformation multiple testing correction method ANOVA false positive rate Kruskal Wallis test between group comparison objective between group comparison statistical test Dunn’s multiple comparison test ## Default S3 method: dunnTest(x, g, method = dunn.test::p.adjustment.methods[c(4, 2:3, 5:8, 1)], two.sided = TRUE, altp = two.sided, ...) from: http://www.rforge.net/doc/packages/FSA/dunnTest.html Dunn's test Dunn, O.J. (1961) Multiple comparisons among means. JASA, 56: 54-64 Dunn, Olive Jean (1964). "Multiple comparisons using rank sums". Technometrics. 6 (3): 241–252. doi:10.2307/1266041 and adapted from: http://www.statisticshowto.com/dunns-test/ Dunn’s Multiple Comparison Test is a post hoc (i.e. it’s run after an ANOVA) non parametric test (a “distribution free” test that doesn’t assume your data comes from a particular distribution). It is one of the least powerful of the multiple comparisons tests and can be a very conservative test–especially for larger numbers of comparisons. The Dunn is an alternative to the Tukey test when you only want to test for differences in a small subset of all possible pairs; For larger numbers of pairwise comparisons, use Tukey’s instead. Use Dunn’s when you choose to test a specific number of comparisons before you run the ANOVA and when you are not comparing to controls. If you are comparing to a control group, use the Dunnett test instead. Philippe Rocca-Serra p-value ready for release