Multi-level Modeling 

Q-Step is a £19.5 million programme designed to promote a step-change in quantitative social science training. Over a five-year period from 2013, fifteen universities across the UK are delivering specialist undergraduate programmes, including new courses, work placements and pathways to postgraduate study. Expertise and resources will be shared across the higher education sector through an accompanying support programme, which will also forge links with schools and employers.

Glasgow Q Step Centre

Multi-level Modeling Mark Tranmer, Professor of Quantitative Social Science, University of Glasgow. Email: mark.tranmer@glasgow.ac.uk August 20th-22nd 2018, The University of Glasgow.
Sessions will take place in Lab M, 1105, Adam Smith Building
 Course Description: We will begin by examining the basics of a two-level model. From there we will proceed to the analysis of other hierarchical structures with several levels and then onto complex non-hierarchical population structures, including cross-classified and multiple membership models. We look at examples for the use of multilevel models with longitudinal data and social network data. Throughout the course, we will look at examples based on substantive research questions, and will include hands-on computing sessions to practice the application of the various approaches. The main software used is R – and also MLwiN with R, through the packages MLwiN, as will be explained. We will look other R packages that enable more complex multilevel models to be fitted, including R2WinBUGS and R2OpenBUGS – which work with WinBUGS and OpenBUGS respectively, and also the MCMCglmm package. Prerequisites: Students should be familiar with basic statistical methods including OLS regression analysis. Familiarity with the basics of logistic regression would also be an advantage, though I will briefly review this, prior to giving details of the multilevel logistic regression model. Suggested Texts: Snijders T and Bosker B (2012) Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modelling. Sage Publications. Further Reading: Chapter 6 of Crossley N, Bellotti E, Edwards G, Everett MG, Koskinen J, Tranmer M (2015) Social Network Analysis for Ego-Nets. Sage Publications. 
ICPSR Summer Program 2018 Course Topics: 1. Introduction to Multilevel Models. 2. Random Intercept Models. 3. Random Slope Models. 4. Logistic Multilevel Models 5. Other non-linear multilevel models. 6. Cross-Classified Models. 7. Multiple Membership Models. 8. Multilevel Models for Longitudinal Data 9. Use of Multilevel Models with Social Network Data (outline) 10. Alternative Software. Instructor - Biographical Sketch Mark Tranmer is Professor of Quantitative Social Science in the School of Social & Political Sciences University of Glasgow. His methodological research focus began in multilevel modelling to assess geographical and organisational variations in individual responses of interest. Recently, he has been interested in developing multilevel approaches to estimate social network variations in individual level responses. He has further extended these approaches to assess changes over time in these variations. These methodological developments highlight his general interest in understanding social population structure from a geographical, organisational, network, and temporal perspective. Substantive applications of these methods include assessing individual and area variations in the take-up of post-compulsory education, inequalities in health and well-being, variations in crime by local area, variations in civic and political engagement in the UK and Europe, changes in occupational tie structures in the UK over time, network variations in hospital waiting times and patient safety, and area, school, and network variations in drinking, smoking and drug use in six European countries. He has published in a range of substantive and methodological journals. He was recently guest co-editor of a special edition of “Social Networks” on Multilevel Social Networks. He has honorary senior and professorial positions at the Universities of Stirling, Wollongong (Australia) and USI (Switzerland). He has also taught a range of statistical methods courses at various levels in the UK and internationally to academic and non-academic audiences, He leads the Glasgow Quantitative Methods Group (GQMG), which promotes the interdisciplinary use of quantitative methods in research & teaching. https://twitter.com/G_Q_M_G Example publication (involving more advanced multilevel models): Tranmer M., Steel, D. and Browne, WJ (2014) Multiple-membership Multiple-Classification Models for Social Network and Group Dependencies. Journal of the Royal Statistical Society: Series A (Statistics in Society), vol. 177,no. 2, pages 439-455.

Lab M (ASB1105)

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Multi-level Modeling

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