Multilevel Modelling - Virtual Classroom

Date: Wednesday 24 February 2021, 10.00AM
Location: Online
CPD: 12.0 hours
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Level: Professtional (P)

This two-day virtual 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.
 

Level: Professtional (P)

This two-day virtual 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 and longitudinal data

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

Topics Covered

  • Overview of multilevel modelling

  • Variance-component models

  • Random-intercept models

  • ​Within - and between - cluster effects of the covariates

  • ​Three-level models

  • Random slope models

  • Growth-curve models for repeated measures longitudinal data

  • Multilevel logistic regression for binary response data

  • Resources continuing your multilevel modelling learning after the course
     

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!”

 

Professor George Leckie

George is a Professor of Social Statistics and Co-Director of the Centre for Multilevel Modelling at the School of Education, University of Bristol, UK.

His methodological interests are in the development, application and dissemination of multilevel and related models to analyse educational and other data. His substantive interests focus on design, analysis, and communication issues surrounding school performance measures and league tables, especially the use of value-added models for estimating school effects on student achievement for accountability and choice purposes.

He was awarded the Frances Wood Medal in the Royal Statistical Society's 2017 honours for his contributions to Social Statistics over the past 10 years, especially his school league table research.

George has taught over 50 multilevel modelling short courses across UK, Europe, Australia and US.

 

Professor William J Browne

Bill is a professor of statistics at the University of Bristol. His research spans the area of statistical modelling, from the development of statistical methods to fit realistically complex statistical models to describe real-life problems, through the implementation of those models in statistical software to the application of the methods in several application areas.

Much of his computational work has been in the development of statistical software within the Centre for Multilevel Modelling and in particular in the development of the MLwiN and StatJR packages.

His methodological work has been with regard MCMC methods for fitting these multilevel models and also for tailoring MCMC algorithms for specific other models.

He has  worked on applying multilevel and other statistical models to problems as diverse as assessing welfare in chickens, modelling herd breakdowns with TB in cattle, investigating nesting behaviour of great tits and the impact of class sizes on primary school children.
 

 

Fees

   

Registration before
 24 January 2021

 

Registration on/after
 24 January 2021

                                  

Non Member 

RSS Fellow 

RSS CStat/Gradstat also MIS & FIS

 

£611.00+vat 

£520.00+vat 

£490.00+vat

£680.00+vat 

£577.00+vat 

£543.00+vat