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Applied Multilevel Modelling 2017

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Applied Multilevel Modelling

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.

  • 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.

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

Participants are expected to have a good working knowledge of simple statistical methods, including a good understanding of linear regression. No familiarity with the software MLwiN is required.

Course Code

NCRM7240

Course Dates

13th September 2017 – 15th September 2017

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Course Leader

Dr Ian Brunton-Smith
Course Description

Programme dates - more details to follow

13th September 2017 (9:30am – 5.30pm)

14th September 2017 (9:00am – 4.30pm)

15th September 2017 (9.00am – 4.00pm)

 

 

 

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