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.
COORDINATORS:
General outline
Prerequisites
Epidemiology, Mathematical Foundations for Biostatistics, Principles of Statistical Inference, Regression Modeling for Biostatistics 1
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.
Special Computer Requirements
R or Stata statistical softwareContent
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.
Resources
Course notes, online mini-lecture videos, online tutorials, discussion board