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!
 



       
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