LSC Course - LING698D: Hierarchical Model Foundations in R
October 20, 2026
Expand your quantitative research toolkit this winter with this hybrid course!
The Language Science Center is excited to offer LING698D: Hierarchical Model Foundations in R this winter! In this course, students will apply hierarchical models to the kind of data they typically work with, use data simulation techniques to interpret models, and learn strategies for common challenges in fitting and interpretation.
- Term: Winter 2027, January 4-22, 2027
- Instructor: Scott Jackson
- Days & Times: Monday through Friday, 5 days/week, 10:00 AM -11:00 AM
- Location: Hybrid, 2123 H.J. Patterson Hall (Students can attend in person or online)
Note: Please refer to the location listed above, as Testudo may temporarily show a different room
Course description: (1 credit) Regression models are one of the most flexible and ubiquitous tools in a data analyst's toolkit, especially considering how they can be extended. One of the most widely applicable class of extensions includes hierarchical models, also known as mixed-effects models or multi-level models. By including so-called random effects, these models are a good fit for many types of grouped or clustered data, such as repeated measures experimental designs or observational/survey designs with grouping or stratification factors. In this course, students will apply and interpret these models for relevant data within their fields. The course will emphasize typical challenges with fitting and interpreting hierarchical models and students will apply practical strategies for managing these challenges. This will include practice with both traditional and Bayesian tools for computation, as well as data simulation techniques. This course assumes basic knowledge of R, and is best suited for students who have some experience with regression or ANOVA models, but it does not require any prior knowledge of hierarchical models.
Registration is open now. Reserve your spot today!