Foundations of Regression

This subject provides the foundation for understanding and using regression methods in biostatistics. Students will learn what a regression model is and how regression methods are used for the major purposes of research investigations: description, prediction and causal inference. The emphasis will be on learning how to build, fit and interpret regression models for these different purposes, focusing on linear regression for continuous outcomes and logistic regression for binary outcomes, and including treatment of key issues such as model fit, parametrisation and interaction. Important underlying mathematical concepts will be covered, such as the method of least squares, maximum likelihood estimation and matrix algebra representation of multiple regression.