EPM5009

Categorical data and generalised linear models ( 6 points, SCA Band 2, 0.125 EFTSL)

Leader: Prof A. Dobson

Offered:
Clayton Second semester 2005 (OCL)
MMS-ALFRED Second semester 2005 (OCL)

Synopsis: This unit 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. 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.

Objectives: On completion of this unit students should be able to: 1. understand the major theoretical aspects of generalised linear models; 2. appreciate regression modelling strategies for generalised linear models; 3. including estimation issues, choice of models, prediction and goodness of fit of a selected model; 4. be proficient in the analysis of binary outcome data, either form a standard study design or from a matched study design; 5. be capable of analysing ordered and unordered categorical outcomes using simple measures of association and complex regression models; 6. be capable of analysing count data whether it satisfies standard distributional assumptions or whether it is over dispersed.

Assessment: Two written assignments + Selected practical exercises

Prerequisites: MPH1040, EPM5002 & EPM5003

Corequisites: EPM5004