I have the following design: 60 Plants assigned to treatment A (with, without) Variables V1 and V2 have been measured at the plant level (e.g. biomass) We selected three leaves per plant (young, intermediate, old) and measured three variables per leaf (V3, V4, V5). Thus, we have a kind of split-plot design. We now want to know how treatment A affects "plant phenotype" which is characterized by variables V1, V2 (plant level) and V3-V5 (leaf level). Of course, we can use a linear model for each variable separately, but we need to have a measure how the plant "as a whole" was affected by A. We think that analyzing dissimilarity matrices from all plant traits might be a good option to assess the effect of A. In R, there is a package available (adonis) which does a "permutational MANOVA". I wonder if there is something similar possible in SAS. Further, I am not sure how to deal with the split-plot structure of leaf data in such permutation tests. Many thanx for every idea!!!!
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