I want to perform an ANCOVA analysis of data concerning density of plant epiphytes. At first, I would like to know if there is any difference in plant density between two slopes, one N and one S, but I have other data such as altitude, canopy openness and height of the host plant. I know that my covariate would have to be the two slopes (N and S). I built this model that runs in R and although I have no idea if it performs well. Also I would like to know what the difference is if I use the symbol
model1 <- aov(density~slope+altitude+canopy+height) summary(model1) model1
The basic tool for this is
lm; note that
aov is a wrapper for
In particular, if you have some grouping variable (factor), g, and a continuous covariate x, the model
y ~ x + g would fit a main effects ANCOVA model, while
y ~ x * g would fit a model which includes interaction with the covariate.
aov will take the same formulas.
Pay particular attention to the
Note in the help on
*, russellpierce pretty much covers it, but I’d recommend you look at
?formula and most especially section 11.1 of the manual An Introduction to R that comes with R (or you can find it online if you haven’t figured out how to find it on your computer; most easily, this involves finding the “Help” pull down menu in either R or RStudio).