Hi R users! I have the following problem: how appropriate is my aov model under the violation of anova assumptions?
Example: a<-c(1,1,1,1,1,1,1,1,1,1,2,2,2,3,3,3,3,3,3,3) b<-c(101,1010,200,300,400, 202, 121, 234, 55,555,66,76,88,34,239, 30, 40, 50,50,60) z<-data.frame(a, b) fligner.test(z$b, factor(z$a)) aov(z$b~factor(z$a))->ll TukeyHSD(ll) Now from the aov i found that my model is unbalanced, and from the flinger test i found out that the assumption of homogeneity of variances is rejected. Could my Tukey comparison be a valid one under these violations? From what i read the Tukey test is valid only when the model is balanced and when the assumption of homogeneity of variances is not rejected, am i wrong? Can anyone tell me what would be the correct test in this case? Doing a non-parametric Kruskal - wallis test would give me a different result. But what would be the correct multiple comparison test in this case? Thank you and have a great day ahead! --------------------------------- [[alternative HTML version deleted]] ______________________________________________ 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.