The aim of this unit is to enable students to apply methods based on linear models to biostatistical data analysis, with proper attention to underlying assumptions and a major emphasis on the practical interpretation and communication of results. This unit will cover: the method of least squares; regression models and related statistical inference; flexible nonparametric regression; analysis of covariance to adjust for confounding; multiple regression with matrix algebra; model construction and interpretation (use of dummy variables, parametrisation, interaction and transformations); model checking and diagnostics; regression to the mean; handling of baseline values; the analysis of variance; variance components and random effects. NOTE: Linear Models is an important foundation unit. Students who do not develop a strong grasp of this material will struggle to become successful biostatisticians.
8-12 hours total study time per week
Two major assignments worth 30% and 40% and two shorter assignments worth 10% and 20%.
No compulsory textbook
BSTA5023 and (BSTA5011 or PUBH5010)Co-requisites