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:
Dr John Holmes University of Melbourne, School of Population and Global Health Semester 1
Prof Lyle Gurrin University of Melbourne, School of Population and Global Health Semester 1
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