This is an open online live course
Open online live course: Introduction to Linear Mixed-Effects Models and GLMM with R.
- Dates: 28, 29, 30 and 31 October 2024.
- Times: 09.00 - 16.00 UK time.
- Included: 1 hour face-to-face video chat about your data. See flyer for details and conditions.
Course format
- Live online teaching is from 09.00-16.00 UK time.
- The course includes a few theory presentations along with a large number of exercises using real data sets.
- Detailed, annotated R code will be provided, and a brief period will be set aside for practice before each exercise is discussed in depth.
- On-demand video files are available. Self-study is an option.
Brief outline
The course begins with a brief review of multiple linear regression and generalized linear models. This is followed by an introduction to linear mixed-effects models and generalized linear mixed-effects models (GLMM) for analyzing hierarchical or clustered data. Examples of such data include multiple observations from the same animal, site, area, nest, patient, hospital, vessel, lake, hive, transect, and so forth. These statistical techniques are designed to address dependency within your data.
In the second part of the course, we apply GLMMs to various types of data. This includes continuous data (e.g., biomass), binary data (e.g., the presence or absence of a disease), proportional data (e.g., % coverage), and count data. For these analyses, we employ several distributions: Poisson, negative binomial, Bernoulli, binomial, beta, Tweedie, and gamma.
For more information, see the course flyer: Flyer2024_11_GLMM_Online