I have a dataset with a categorical treatment (1 if treated, 0 if control) and many columns (34) of response variables. Each column represents a species and its response (some measured abundance) to the presence or absence of the treatment. Each row is a separate site; exactly half of them were treated and the other half were controls. The experiment was replicated over two years.
I am interested in finding out which of these species respond to the treatment, so a LDA was suggested, but I am confused because my treatment is categorical and all of the examples I can find of LDA use continuous predictor variables.
So the data look like:
Treatment(0/1) Site(ID#) Year(1/2) Species 1 Species 2 ... Species 34
Can I use a LDA for this question? If not, what sort of ordination is capable of accounting for categorical predictor variables?