
Multilevel models (MLMs) have become increasingly popular in public health and the social sciences for analysing data organised in nested levels (e.g., residents of neighbourhoods) or data with repeated measurements (e.g., longitudinal data). These models can be viewed as an extension of conventional linear and logistic regression models to account for and learn from the clustering in the data. In this workshop, Gavin will focus on these concepts along with worked examples to demonstrate the fundamental principles of MLMs.
For registrations and more information please email: uchri@canberra.edu.au
The workshop is divided into two sections. Section 1 introduces the conceptual, methodological, statistical, and analytic basis of MLM. In this section, we examine the ‘what and why’ of MLM, multilevel data structures, clustered data and statistical inference, composition and context, modelling averages and variation around the average, appropriate model specification, partitioning variance, and random intercept and random slope models.
Section 2 presents worked examples of MLM from public health and transport research, demonstrating each of the components of Section 1. Specifically, we examine the neighbourhood-built environment and body mass index using multilevel linear regression, car ownership using binary multilevel logistic regression, and number of cars owned using multilevel multinomial logistic regression.
Throughout the workshop Gavin will draw on data and examples from neighbourhood-based research. However, the material presented (and its interpretation) is equally applicable to all situations where observations are clustered (e.g., students in classes, patients in hospitals, employees in workplaces).
The workshop assumes no prior knowledge of MLM, but participants will get the most out of the session if they have a basic understanding of topics such as statistical inference, variance and standard errors, significance testing, linear and logistic regression models.
At the end of the workshop participants will have a greater understanding of the basic principles of MLM and of the notion of modelling contexts (e.g., neighbourhoods), and be able to conceptualise MLM strategies, and (hopefully) implement MLMs and interpret the output.
Gavin Turrell is a Professor in the Healthy Liveable Cities Lab at the Centre for Urban Research, RMIT and Adjunct Professor at the Health Research Institute. His primary research interests are in social epidemiology, with a focus on the social determinants of health and health inequities.