Categorical Data and Generalised Linear Models
This course will explore biostatistical applications of generalised linear models with an emphasis on underlying theoretical issues, and practical interpretation of the results of fitting these models. This course is offered in conjunction with the Biostatistical Collaboration of Australia (BCA).
|Faculty||Faculty of Health and Medicine|
|School||School of Medicine and Public Health|
Semester 2 - 2015
(Distance Education - Callaghan)
On successful completion of this course, students will be able to:
Generalised linear models are a family of models with a unified theory for estimation and inference, including as special cases many of the commonly-used methods in the analysis of health data. Because of the central importance of binary outcomes in epidemiological studies, a thorough grounding in relevant methods for 2x2 and 2xk tables will be given and this will extend naturally into logistic regression for a binary outcome as a special case of generalised linear modelling. A full introduction into measures of association and modelling techniques for ordinal outcomes will be presented. A grounding in methods for analysing count data will be provided. Techniques for dealing with matched data, e.g from case-control studies, will also be introduced.
|Assumed Knowledge||Epidemiology (EPID6420); Mathematical Background for Biostatistics (BIOS6040); Principles of Statistical Inference (BIOS6050); Probability and Distribution Theory (BIOS6170); Linear Models (BIOS6070) Co-requisite. Please note, Program Coordinator approval is required for taking CDA and LMR simultaneously.|
|Timetable||2015 Course Timetables for BIOS6020|