AQM: Introduction to Multilevel Modelling

Advanced Quantitative Methods (AQM) Training for all Pathways

Multilevel models allow researchers to use data that has a multilevel structure, such as pupils within schools, individuals within neighbourhoods, or longitudinal panel data where observations are nested within individuals. A failure to take account of such structures can lead to results that are not only biased or anticonservative, but also missing important aspects of the societal processes they are trying to uncover. This course will build on standard regression models to provide an introduction to 2-level multilevel models that can be used in a range of disciplines across the social sciences and beyond.

Participants will gain experience using relatively simple multilevel models, and be pointed to resources for more complex models.

Workshop leader

Dr Andrew Bell is a Lecturer in Quantitative Social Sciences and the Director of the WRDTP Advanced Qualitative Methods Training and Development Group. Andy was a lecturer at the University of Bristol, where he also completed his undergraduate degree (in Geography) and PhD (in Advanced Quantitative Methods). Andy’s research interests include multilevel modelling, longitudinal modelling, mental health and wellbeing, life course research, political science, social epidemiology.

Learning Outcomes

Learn how to implement multilevel models for data with two levels and a continuous Y variable. This will include random intercept models, and random slopes models, that allow the effect of a variable to vary across higher-level units.
Learn how to use the MLwiN software to implement multilevel models
Learn how to produce a range of plots to visualise multilevel effects

PLEASE NOTE: Students are responsible for arranging travel to and from this AQM training session. The WRDTP cannot reimburse travel costs in this instance.

This is an Advanced Qualitative Methods (AQM) training workshop open to PhD students aligned with any of the 7 interdisciplinary Pathways.

Prerequisites

Participants must have a good understanding of multiple regression modelling and inferential statistics, especially regression intercepts and slops, standard errors, t-ratios, residuals and the concepts of variance and co-variance. No experience of multilevel modelling, or MLwiN, is expected. As a check, participants should be comfortable with completing module 3 of the LEMMA online course that can be found here: LEMMA

For any queries regarding this training session please contact Andrew Bell via andrew.j.d.bell@sheffield.ac.uk