Curriculum
Longitudinal and Correlated Data (LCD)
To enable 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 produce non-exchangeable outcomes.
Coordinator
Dr John Holmes and Prof Lyle Gurrin Melbourne School of Population & Global Health, University of Melbourne
COORDINATORS:
General outline
Prerequisites
Epidemiology, Mathematical Background for Biostatistics, Probability and Distribution Theory, Principles of Statistical Inference, Linear Models, Categorical Data and Generalised Linear Models
Time commitment
8-12 hours total study time per week
Semester availability
Semester 1
Assessment
Assignments 100% (two major assignments worth 30% each (8 hours) and 5 shorter assignments each worth 8%.
Prescribed Texts
Recommended – not compulsory: Fitzmaurice G, Laird N, Ware J. Applied Longitudinal Analysis. John Wiley and Sons, 2011. For details, including ISBN, see the BCA Textbook and Software Guide
Special Computer Requirements
Stata statistical software
Content
Paired data; the effect of non-independence on comparisons within and between clusters of observations; methods for continuous outcomes: normal mixed effects (hierarchical or multilevel) models and generalised estimating equations (GEE); role and limitations of repeated measures ANOVA; methods for discrete data: GEE and generalized linear mixed models (GLMM); methods for count data.
Special Computer Requirements
Course notes, assignment material and interaction facilities available online