So I calculated the beta diversity for my experiment. The p-values tell me that all are significantly different. My question is: would it be possible to apply a post-hoc test to rank the treatments based on the distance value so that I can see which has the highest distance and which the lowest distance? Or perhaps this is not possible?
Thank you for your support.
This visualizer will compare all groups report which pairs are significantly different:
You can sort by distance using your the means you have in that boxplot. Is that what your asking about?
Thanks a lot for your response! I have indeed used the bega group significance plug-in and I obtained pairwise comparisons.
So what you are saying is that I can just use the median distance of each box plot and then rank them from highest to lowest? Just trying to follow your reasoning.
Thanks for the support.
Yeah, that was first thought. Sorting by means or medians seems reasonable… but I’m not a statistician! You should probably get their advice and see if there is an established test for this method.
I just googled “post-hoc test rank by distance” and found this paper. With >500 citations, that could be a good thought.
I know @mortonjt had stats experience. Maybe he can point us in the right direction.
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@Pablo_V, I’m not sure this question has been answered or not, but is there a reason why the standard PERMANOVA test cannot be applied here? That would provide F-statistics for all pairwise comparisons, which you can then sort by effect size (i.e. the F-statistic).