Longitudinal and Correlated Data
Enables students to apply appropriate methods to the analysis of data arising from longitudinal (repeated measures) epidemiological or clinical studies, and from studies with other forms of clustering (cluster sample surveys, cluster randomised trials, family studies) that will provide non-exchangeable outcomes. This course is offered in conjunction with the Biostatistics Collaboration of Australia (BCA).
|Faculty||Faculty of Health and Medicine|
|School||School of Medicine and Public Health|
Semester 1 - 2014
(Distance Education - Callaghan)
Previously offered in 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004
At the completion of this course students should be able to:
The concept of hierarchical data structures will be developed, together with simple numerical and analytical demonstrations of the inadequacy of standard statistical methods. Beginning with the normal-theory model, more appropriate statistical procedures involving mixed linear models will be developed and explored using the SAS or Stata statistical software packages. Extensions to non-normal outcomes will be demonstrated in which emphasis will be placed on the clinical research question. Using a set of case studies, generalised estimating equations and generalised linear mixed models will be developed and contrasted. The limitations of traditional repeated measures analysis of variance will be demonstrated, together with an introduction to non-exchangeable models.
|Assumed Knowledge||Epidemiology (EPID6420); Mathematical Background for Biostatistics (BIOS6040); Probability and Distribution Theory (BIOS6170); Principles of Statistical Inference (BIOS6050); Linear Models (BIOS6070); Categorical Data & GLMs (BIOS6020);|
|Modes of Delivery||Distance Learning : Paper Based
|Teaching Methods||Self Directed Learning|
|Course Materials||None listed|
|Timetable||2015 Course Timetables for BIOS60901|