15 Logistic Regression

In this session, we continue exploring regression modelling. We now extend the ideas encountered in the context of linear regression models and apply them to a setting where the outcome of interest is a binary variable.

Intended learning outcomes

By the end of this session, you will be able to:

  • explain the rationale and the structure behind the logistic regression

  • apply a logistic regression model to real data

  • interpret the results of a logistic regression

  • interpret output from key diagnosis tools used for logistic regression

14.7 Proofs 15.1 Regression modelling for binary outcomes