Linear mixed effects models
11, 18 October 2024 | 09:30 - 17:00 BST | Check Your Timezone
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Instructors: Vicki Hodgson, Martin van Rongen (Bioinformatics Training Facility), Soumya Banerjee (Department of Computer Science and Technology), Camice Revier (Department of Psychiatry), Betty Wang (Clinical Neurosciences)
UTBS event page: https://training.cam.ac.uk/bioinformatics/event/5342290
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.
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
Additional scripts relating to the course can be found here.
Before the course
Please feel free to introduce yourself in the 'Introductions' document linked above before the course, so that the tutors may understand your background and interest in linear mixed effects models.
Software
You will have access to PCs to use during the course if you wish. However, we encourage you to bring your own laptop so you can set it up and practice on it if you would like. You will have access to the University wifi service in the teaching room.
Please ensure that you have RStudio/R installed prior to the course. Installation instructions can be found on the Course materials page.
Training room address
Craik-Marshall Building
Downing Site
Cambridge, CB2 3EB
Timetable
Date Time Topics
Fri 11th October 09:30 - 13:00 Random effects, fitting & visualising simple models
Fri 11th October 14:00 - 17:00 Significance testing & checking assumptions
Fri 18th October 09:30 - 13:00 Nested & crossed random effects
Fri 18th October 14:00 - 17:00 Using mixed models for complex designs (& your own data)
Feedback survey
https://www.surveymonkey.com/r/Z6G65HK
This course is still new - so we'd really like your feedback! Let us know what you liked, what could be improved, and whether you feel the course has benefited you.
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