This two-day course provides an introduction to multilevel modelling and includes software practicals and demonstrations in R. We focus on multilevel models for continuous and binary outcomes when data are clustered (nested or hierarchical). These models extend conventional linear and logistic regression by accounting for—and learning from—the clustering in the data. They are appropriate, for example, when analysing exam scores for students nested within schools, health outcomes for patients nested within hospitals, or attitudes of respondents within areas. Particular emphasis is placed on disentangling processes operating at different levels of analysis by decomposing the within- and between-cluster effects of explanatory variables (covariates). Longitudinal data also have a clustered structure, with repeated measurements nested within individuals or multiple panel waves nested within survey respondents. Throughout the course, we emphasise model interpretation and the types of research questions that multilevel models are designed to address.

Professor George Leckie is a Professor of Social Statistics and Co-Director of the Centre for Multilevel Modelling (CMM) at the School of Education, University of Bristol, UK. His methodological interests are in the development, application and dissemination of multilevel and related models to analyse educational and other social and health data. He has authored over 100 journal articles, many developing or applying multilevel modelling. He has taught over 90 multilevel modelling short courses across UK, Europe, Australia and US.