Linear mixed effects models (IN-PERSON)
Date: 15 - 16 July 2025
Note: This iteration of the course is currently not open for booking. However, please register your interest here to be notified when spaces become available. Your registration ensures you will be the first to know.
This course gives an introduction to linear mixed effects models, also called multi-level models or hierarchical models, for the purposes of using them in your own research or studies.
We emphasise the practical skills and key concepts needed to work with these models, using applied examples and real datasets.
After completing the course, you should have:
* A conceptual understanding of what mixed effects models are, and when they should be used
* Familiarity with fitting and interpreting mixed effects models using the lme4 package in R
''Please note that this course builds on knowledge of linear modelling, therefore should not be considered a general introduction to statistical modelling.''
If you do not have a University of Cambridge Raven account please book or register your interest here.
Additional information
- ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
- Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
- Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
- Further details regarding eligibility criteria are available here.
- Guidance on visiting Cambridge and finding accommodation is available here.
Keywords: HDRUK
Venue: Craik-Marshall Building
City: Cambridge
Country: United Kingdom
Postcode: CB2 3AR
Organizer: University of Cambridge
Host institutions: University of Cambridge Bioinformatics Training
Target audience: Everyone is welcome to attend the courses, please review the policies.
Event types:
- Workshops and courses
Activity log