Applied Multilevel Modelling
Venue: Highfield Campus, University of Southampton, UK
Presenter: Dr Ian Brunton-Smith and Dr Gabriele Durrant
Dates of Course: Wednesday 23rd - Friday 25th January 2013
This course has already run. Please check the course listings for a future course.
Summary of Course:
This course will focus on the application of multilevel models to hierarchically clustered data structures. Topics will include types of multilevel data structures, linear multilevel and logistic multilevel models, random intercept and random slope models, and the use of graphical methods to display results. The course will focus primarily on situations where the dependent variable is continuous, but methods will also be introduced for dealing with binary response data. The course will include a mixture of lectures and practical workshops using the multilevel modelling software MLwiN.
By the end of the course participants should:
- Have a practical understanding of the ideas and methods of modelling data with a multilevel data structure, and know when their use is appropriate
- Have a detailed understanding of how to critically interpret results from multilevel models
- Gain a working knowledge of the multilevel statistical package MLwiN
- Be able to apply these methods to continuous and binary response data
- Multilevel data structures
- Random intercept and random slope models
- Contextual effects and cross-level interactions
- Diagnostic checking and model specification
- Binary response models
- Repeated measures analysis and non-nested data
The course will have a practical emphasis with computer workshops allowing participants to work through examples using the MLwiN software.
The course is aimed at researchers who want to perform multilevel modeling and have to work with clustered data. Participants may be academic researchers in the social and health sciences or may work in government, survey agencies, official statistics or the voluntary or private sector.
Participants are expected to have a good working knowledge of simple statistical methods, including a good understanding of linear regression (such as provided by the two CASS courses ‘Survey Data Analysis II: Introduction to Linear Regression Modelling' and ‘Regression Methods'). No familiarity with the software MLwiN is required.
There are an increasing number of good introductory multilevel books. Below are a few that participants may find useful before attending the course.
- Hox, J (2002) Multilevel analysis: Techniques and applications. Lawrence Erlbaum Associates. Mahwah, New Jersey, ISBN 080583219X
- Bickel, R (2007) Multilevel Analysis for Applied Research. It's Just Regression! The Guildford Press. New York. ISBN 159385191X
- Snijders, T and Bosker, R (1999) Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modelling. Sage Publications, London, ISBN 0761958908
Participants should also check the online material at the Centre for Multilevel Modelling at the University of Bristol (http://www.cmm.bristol.ac.uk/). The site provides a range of introductory training material. Students and academics can also download the MLwiN software from here free of charge.
Participants will receive written course notes.
Please bring a calculator for the workshops as well as a USB memory stick for saving your computer workshop output.
Dr Ian Brunton-Smith is a lecturer in quantitative methods in the Department of Sociology at the University of Surrey. He has also worked as a criminologist in the Crime Surveys team at the Home Office. He has research interests in the impact of neighbourhood effects on individual outcomes, interviewer effects, and cross-national research. He has also published on the effects of panel conditioning on survey outcomes, how to measure crime, and multilevel meta-analysis. He completed his PhD in Social Statistics at the University of Surrey and has an MSc in Social Research Methods and a BA in Criminology.
Dr Gabriele B. Durrant is a Senior Lecturer at the Southampton Statistical Sciences Research Institute (S3RI) at the University of Southampton. She is the principal investigator of two 3-year ESRC-funded research grants in the UK, one on paradata and one on nonresponse analysis. She has research interests in the analysis of paradata, interviewer effects, nonresponse in sample surveys, measurement error, and statistical modelling in the social sciences, in particular multilevel modelling. She is guest editor of a special issue on paradata of the Journal of the Royal Statistical Society, Series A, Associate Editor of JRSSA and member of the committee of the Royal Statistical Society Social Statistics Section. Gabriele has taught a wide range of statistical courses, primarily short courses at postgraduate level, including courses for professional development. She completed her PhD in Statistics at the University of Southampton and has a BSc and MSc in Mathematics and Geography.
£30 per day for UK-registered students. £60 per day for staff from UK academic institutions (including research centres), ESRC funded researchers and UK registered charitable organisations. £220 per day for all other participants. The course fee includes course materials, lunches and morning and afternoon refreshments. Travel and accommodation are to be arranged and paid for by the participant.
Location and Accommodation:
The course will be held at the Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Southampton, SO17 1BJ. Participants will need to make their own accommodation arrangements. Further information on accommodation and course location is available here.
On the first day, the course will start with registration and coffee at 9.30 with formal teaching starting at 10.00 a.m. On the last day, formal teaching will end at about 2.30p.m. Afterwards there will be an opportunity for participants to ask questions about the course and to discuss with the instructor how to analyse their own data (until about 4pm). (Participants are welcome to bring their own data if they wish).