NCRM – Random Effects Modelling – Advanced Issues

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Random effects models are applied in a range of social science domains (e.g. education, health and economics). Across disciplines, however, they are often used for different purposes, with different specifications, or even with different terminologies. These differences may well reflect genuine complexities and ambiguities that are associated with their implementation. This two-day course will focus on selected advanced issues in the application of random effects models in social research contexts. It is most suited to empirical social science researchers with some previous experience in using statistical models with random effects.

Presenter: Professor Paul Lambert

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The course will

• Review common uses of random effects models in the social sciences
• Explore enduring debates in the specification and exploitation of random effects models
• Facilitate virtual lab sessions designed to illustrate and investigate the contribution of random effects models

Participants will be supported in order to

• Secure a rigorous understanding the terminology and features associated with random effects models
• Understand different perspectives in important debates concerning the use of random effects
• Enhance practical skills in applying random effects models to statistical datasets

Participants should have experience of estimating statistical models including some previous experience working with random effects models, for instance through multilevel modelling, frailty modelling or longitudinal and panel models.

The participants will be invited to use their own computers in the virtual lab exercises. Participants should have at least one of the software packages Stata, SPSS and R installed on their computers in order to participate in the virtual labs.

The course will be delivered on-line and run from 10:00 – 16:00 each day.