Longitudinal and Correlated Data

Monday, 11 February 2013 to Wednesday, 13 February 2013
9.00am to 5.00pm
Melbourne School of Population Health
The University of Melbourne 207 Bouverie Street
Carlton 3054

Monday 11 February & Tuesday 12 February
Presenters – Prof John Carlin & Prof Andrew Forbes

Days 1 and 2 will provide an introduction to the theory and application of the statistical methods that are commonly used for analysing longitudinal and correlated data from epidemiological or clinical studies (e.g. cluster randomised trials, longitudinal cohort studies). These methods include generalised estimating equations (GEEs) and generalised linear mixed-effects models. Participants will also learn how to implement the methods presented through a series of practical computing exercises with examples in Stata and R.

Wednesday 13 February
Presenter – A/Prof Lyle Gurrin

On Day 3, participants will be provided with an introduction to Bayesian methods followed by an explanation of the application of Bayesian methods to analyse longitudinal and correlated data, building on the data examples presented on days 1 and 2 of the course. The application of Bayesian analyses to data will be demonstrated using the statistical software package WinBUGs.

Professor John Carlin

Prof. John Carlin

Management Team
Clinical Epidemiology and Biostatistics Unit
Murdoch Childrens Research Institute

John holds appointments with the Murdoch Children’s Research Institute and The University of Melbourne.

Since completing a PhD in Statistics at Harvard University he has been engaged as a collaborator in a wide range of medical and public health research, including clinical trials and large-scale epidemiological studies.

His biostatistical research interests have focussed recently on methods for dealing with missing data using multiple imputation.

Professor Andrew Forbes

Prof. Andrew Forbes

Management Team
Department of Epidemiology and Preventive Medicine
Monash University

Andrew is the current Head of the Biostatistics Unit in the Department of Epidemiology and Preventive Medicine at Monash University.

Since completing a PhD in Statistics at Cornell University (USA) he has been actively engaged in collaborative epidemiological and clinical research projects. His research interests are methods for comparative effectiveness research, assessment of the effects of time dependent exposures, interrupted time series designs and methodology in clinical trials.