You are here:

Multilevel Modelling

Organised by

 Royal Statistical Society

Presenter

Professor George Leckie and Professor William J Browne

Date

24/02/2021 - 25/02/2021

Venue

12 Errol Street

Map

View in Google Maps  (EC1Y 8LX)

Contact

training@rss.org.uk

Description

This two-day course is designed to give participants an introduction to the theory and application of multilevel regression models for clustered or hierarchical data using the MLwiN statistical software package. We focus on two-level linear and logistic regression models for cross-sectional (individuals nested within groups) and longitudinal (repeated measures nested within individuals) data. The course consists of a 2:1 mix of lectures and “hands on” practical sessions using MLwiN. Each new modelling development is illustrated with real applications to social, behavioural and medical science data sets.
 

Learning Outcomes

  • An appreciation of the implications of ignoring clustered cross-sectional and longitudinal data structures in statistical modelling

  • An understanding of a range of multilevel regression models for analysing clustered data

  • Practice at estimating two-level linear and logistic regression models in MLwiN, and at interpreting and plotting the results

  • An understanding of the issues raised by missing data and of appropriate methods for dealing with missing data in multilevel models

An understanding of the issues raised by missing data and of appropriate methods for dealing with missing data in multilevel models.
 

Topics Covered

  • Introduction to multilevel modelling

  • Variance-component models

  • Random intercepts models

  • Growth-curve multilevel models for repeated measures longitudinal data

  • Multilevel logistic regression for binary response data

  • Maximum likelihood estimation and Markov chain Monte Carlo methods for fitting models

  • Missing data and multiple imputation methods for multilevel models

  • Resources for multilevel modelling
     

Target Audience

Applied quantitative researchers with an interest in the analysis of clustered cross-sectional and longitudinal data.


Assumed Knowledge

The course will not assume a high level of statistical knowledge, but participants will be expected to have a good understanding and experience of applying and interpreting conventional linear and logistic regression models. A set of on-line training materials to enable participants to refresh their knowledge of these topics are available from the Centre for Multilevel Modelling (CMM) website in Bristol (http://www.cmm.bristol.ac.uk/learning-training/course.shtml).

Delegates will need to download the latest version of MLwiN onto their laptop and bring this to the course, as this will be used during the workshop: http://www.bristol.ac.uk/cmm/software/mlwin/download/


Delegate Feedback

“The course was organised and the topics were well-structured.”

“Good balance of practical & theory, knowledgeable & helpful speakers."

“Excellent course.  Very challenging but pushed me to understand what I needed – I had a breakthrough.  Thank you!”

Level

Advanced (specialised prior knowledge)

Cost

£588 - £816 (inc VAT)

Website and registration

Region

Greater London

Keywords

Quantitative Data Handling and Data Analysis, Multilevel Modelling , Multilevel regression models , Clustered data , Hierarchical data , Longitudinal data , Multilevel models , Growth-curve

Related publications and presentations

Quantitative Data Handling and Data Analysis
Multilevel Modelling

Back to archive...