Course flyer
HYBRID COURSE: This is an onsite course, but you can also join online via Zoom
Location: Maastricht University. Department of System Earth Science. Brightlands Campus Venlo, The Netherlands.
Dates and times: 17-21 August 2026. 09:00-16:00 (local time).
This course is a hands-on introduction to generalised linear mixed effects models (GLMMs) and generalised additive mixed models (GAMMs) in R. The course is delivered onsite, but participants can also join remotely via Zoom.
The course begins with an introduction to linear mixed-effects models, including models with nested structures and random intercepts and slopes. Participants will work through several practical exercises to understand how mixed-effects models are fitted and interpreted. We then introduce GLMMs for analysing non-Gaussian data, including Poisson, negative binomial, and Bernoulli responses.
The next part of the course focuses on generalised additive models (GAMs), which provide a flexible way to model non-linear relationships. Through practical examples, participants will learn how to interpret smoothers, perform model selection, and understand interactions between smooth terms. Building on this, we extend the framework to generalised additive mixed models (GAMMs), combining the flexibility of GAMs with the hierarchical structure of mixed-effects models. Examples include hierarchical GAMs and GAMMs for count data.
In the final part of the course, participants will work with GLMMs and GAMMs for different types of response variables, including continuous data with and without zeros, counts, and proportional data. Distributions covered include Tweedie, Gamma, beta, binomial, Poisson, and negative binomial.
All examples are implemented in R, primarily using the mgcv and glmmTMB packages. The course emphasises practical modelling, interpretation of results, and model validation, rather than mathematical derivations.
The course includes a 1-hour face-to-face video chat with the instructors.
PREREQUISTES
Participants should have working knowledge of R, data exploration, linear regression, and generalised linear models(Poisson and negative binomial).
Participants will receive access to the course website two weeks before the course starts. The website contains approximately 3 hours of preparatory material, including exercises, R scripts, and on-demand videos covering:
- Multiple linear regression
- Generalised linear models
- Model validation using DHARMa
Participants who are not familiar with these topics are encouraged to review the preparatory material before the course begins, as there will be limited time during the course to discuss these basic methods.
If you have questions while working through the preparatory material, you can use the course Discussion Board on the website to ask questions before the course starts.
1 hour face-to-face
The course includes a 1-hour face-to-face video chat with the instructors (to be used after the course). You are invited to apply the statistical techniques discussed during the course on your own data and if you encounter any problems, you can ask questions during the 1-hour face-to-face chat.
A discussion board (access for 12 months) allows for interaction on course content between instructors and participants.
Course content by day
See the flyer: Course flyer
We reserve the right to change the exercises. Pdf files of all theory material will be provided. All exercises consist of data sets and annotated R scripts. Access to the course website is for 12 months.
For terms and conditions, see: