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My input file is organized with sample ID as the row name, and each column representing a certain Operational Taxonomic Unit, with the data being a number for Absolute Abundance of that OTU. I set up the csv file with binary dummy variables to indicate the sample as being one of 3 locations (L1, L2, L3) and one of 6 descriptive categories (D1, D2, D3, D4, D5, D6). Each sample has a 1 for both one of the three L categories and one of the 6 D categories, and zeroes for the other 7 categories they don't belong to. The dummy variables are in the first 9 columns of the data table. When I run the CCA with this formula:

L6DummyVariables.cca <- cca(L6DummyVariables[ ,10:100] ~ L1+L2+L3+D1+D2+ D3+D4+D5+D6,
                            data=L6DummyVariables)

and plot it, there are no vector arrows for L3 and D6. Do I need to change something in my formula? I was told by someone that they are absent because the other vectors are in relation to the missing one, but that does not seem to make sense to me. The other tutorials I have looked at seem to show all of the variables My ordination experience is very limited so my apologies if I'm missing something basic. Thank you! My CCA Plot

Gavin Simpson
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  • If you'd coded `L` and `D` as factors & not dummy variables in your data frame, `cca` would have done the correct thing & produced treatment contrasts for you & would have recorded sufficient information to allow the variables to be correctly represented on the plot. You shouldn't represent categorical vars as arrows here; how would you interpret the arrow? As increasing propensity to be a particular groups? Well that wouldn't hold because there is no such measure in the analysis. Categorical vars like this should be represented as centroids, and **vegan** would do that for you for you... – Gavin Simpson Jul 19 '16 at 21:09
  • @Gavin You should consider posting an answer. You comment is better than my answer. – IRTFM Jul 19 '16 at 21:18

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