As you may have already realised, log-odds are not straight-forward. This is why we use the
predict() function which give us predictions for Y, the dependent variable.
probabilities<-predict(logit.model,type = "response")
The final section include’s the use of the
effects package developed by Fox, et al. The
effects package creates plots for various statistical models. In this example I will show you how it works with a logistic model- but it works with linear models, mixed effects models and many other.
First you have to install the
effects package. The easiest way to visualise your model is by using the
allEffects() function in combination with the
Fox, J. (2003) Effect displays in R for generalised linear models. Journal of Statistical Software 8:15, 1–27, http://www.jstatsoft.org/v08/i15/.