Multilevel modelling for social scientists
Date:
16/03/2020 - 18/03/2020
Organised by:
University of Surrey
Presenter:
Professor Ian Brunton-Smith
Level:
Intermediate (some prior knowledge)
Contact:
Day Courses Administrator
Tel +44(0)1483 689458
Email: daycourses@surrey.ac
Description:
Complex structures exist in the social world and can influence the experiences of individuals – for example, the school you attend can have an impact on the grades you achieve and future life chances, and life expectancy varies dramatically across neighbourhoods, even in the same city. This short course introduces statistical methods for dealing effectively with these types of data structures, enabling us to make robust inferences about the effects of groups, individuals, and the effects of being in a particular group on different individuals.
We will start by covering some of the basic concepts in multilevel modelling and the fundamentals of random intercept and random coefficient models. We will then move on to consider more advanced topics including: nonlinear models for binary responses, repeated measures, and cross-classified models. Throughout the course, the emphasis will be on the practical issues involved in multilevel modelling and the critical interpretation of results, rather than on the underlying statistical derivations. Computer exercises in R will accompany the formal teaching sessions.
Cost:
Varies according to status:
• £595- Government/commercial sector
• £495 - Educational/charitable sector
• £395 - Students.
Website and registration:
https://www.surrey.ac.uk/events/20200316-multilevel-modelling-social-scientists
Region:
South East
Keywords:
Statistical Theory and Methods of Inference, Multi Level Modelling
Related publications and presentations:
Statistical Theory and Methods of Inference