Course overview
This course will enable students to apply methods based on linear and logistic regression models to biostatistical data analysis, with proper attention to underlying assumptions and a major emphasis on the practical interpretation and communication of results. Specifically, this course lays the foundation of biostatistical modelling to analyse data from randomised or observational studies, creating skills that are essential for biostatistics in practice and that will be used by students for the remainder of their BCA studies. This course will introduce the motivation for different regression analyses and how to choose an appropriate modelling strategy. Emphasis will be placed on interpretation of results and checking the model assumptions. Stata and R software will be used to apply the methods to real study datasets.
Course learning outcomes
- See Study Guides at: https://url.au.m.mimecastprotect.com/s/jyzMCmO5QMCjMl1XJtJi1URPVES?domain=bca.edu.au/
- Explain the motivations for different regression analyses and be able to select and apply a suitable modelling approach based on the research aim
- Analyse data using normal linear models, and be able to assess model fit and diagnostics
- Analyse data using logistic regression models for binary data, and be able to assess model fit and diagnostics
- Accurately interpret and manipulate mathematical equations that relate to regression analysis
- Effectively communicate the outcomes and justification of a regression analysis