Date: 20 March 2020
Instructors: Tarani Chandola
Fee: £195 (£140 for those from educational, government and charitable institutions).
CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application.
Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.
This one-day course begins with a description of some examples where multilevel models are useful in statistical analysis and some examples of multilevel populations. We then cover the basic theory of multilevel linear regression models (for continuous dependent variables) including random intercept and random slope specifications, the use of contextual variables in multilevel analysis and modelling repeated measures. This course is suitable for social scientists who want to learn about a quantitative technique that allows both individual and group level variations to be simultaneously taken into account when modelling social phenomena.
- Introduce the general idea of multilevel modelling.
- Consider some issues of multilevel modelling from a substantive and theoretical perspective.
- Show how multilevel modelling can be applied to social data using specialist software MLwiN and R.
No prior knowledge of multilevel modelling is assumed. You will need to have some familiarity with regression models.
- Snijders and Bosker (1999) Multilevel modelling. Sage.
- Goldstein, H. (1995). Multilevel Statistical Models. London: Edward Arnold.
- Dobson, A. (2002). An introduction to generalized linear models. Chapman and Hall
- Rasbash, J., Steele, F., Browne, W. and Goldstein, H. (2015) A User’s Guide to MLwiN, Version 2.33, Centre for Multilevel Modelling, University of Bristol