model.lm <- lm(pa ~ WatrCont + Topo, data = mites)
fitted(model.lm)
# The "fitted()" function gives us expected values for the response variable.
# Some values are lower than 0, which does not make sense for a logistic regression.
# Let’s try the same model with a binomial distribution instead.
# Notice the "family" argument to specify the distribution.
model.glm <- glm(pa ~ WatrCont + Topo, data = mites, family = binomial)
fitted(model.glm)
# All values are bound between 0 and 1.