Research Methods Summer School 2024

The Centre for Literacy and Multilingualism (CeLM) is happy to announce the 7th CeLM Research Methods Summer School, taking place September 2nd-3rd, 2024. Starting in 2017, with a hiatus in 2020 due to the coronavirus pandemic, the CeLM Research Methods Summer School provides advanced training in research methods and statistical analysis for researchers in language, literacy and multilingualism. This year, the summer school will consist of a 2-day online workshop entitled An Introduction to Bayesian Mixed-Effects Models. Dr João Veríssimo (University of Lisbon) will be the tutor for the workshop.

The workshop is open to postgraduate students and early career researchers interested in learning more about these methods. Although the focus is on language research, researchers working in other fields are welcome to attend. Attendance is free, but we only have a limited number of spaces. In case of oversubscription, we will create a waiting list. The workshop will use the statistical software package R and requires some existing understanding of how R works. As such, attendees must have experience of using R. The workshop will provide experience with using the brms package for Bayesian analysis. Attendees do not need prior experience with Bayesian analysis, but must have experience of using mixed-effects models.

To register for the workshop, please complete the online application form before the closing date of August 16th, 2024. Successful applicants will be contacted in due course with further information about the workshops. A preliminary schedule is provided below.

An Introduction to Bayesian Mixed-Effects Models
Dr João Veríssimo (University of Lisbon)

Day 1 (September 2nd): Introduction to Bayesian statistics

Session 1
– Foundations of Bayesian statistics
– Parameters, priors and posteriors

Session 2
– Prior choice recommendations
– Bayesian estimation and credible intervals

Day 2 (September 3rd): Bayesian Hierarchical Models

Session 1: Mixed-effects models
– Fixed and random effects
– Estimating individual differences with random slopes

Session 2: Do we have a good model?
– Choosing a distribution family
– Model checks and model diagnostics