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Cathie Marsh Institute for Social Research (CMI)

Multilevel Modelling

Date: 20 March 2020
Time: 9:30am-5pm
Instructors: Tarani Chandola
Level: Intermediate
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. 

Humanities PGR students at The University of Manchester can apply for a methods@manchester bursary to help cover their costs. All applications will be considered on a case-by-case basis and applicants will be required to provide a supporting statement from their supervisor. Applications for bursaries must be submitted at least two weeks in advance of the course date; applications submitted after this time will not be accepted. Retrospective applications cannot be made if courses have already taken place or payment has already been made.

Please click here to make a booking. If you are applying for a subsidised place, select the £60 University of Manchester option on the booking form. For queries about methods@manchester bursaries, contact (please note, you must have a confirmed place on the course before requesting a bursary application form). For any other queries about short courses, please contact

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.  

Recommended reading 

  • 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

About the instructors