Hierarchical GAMs

This workshop will re-visit random and fixed effects with Hierachical GAMs (HGAMs) and expand the concepts of random slopes by introducing random smooths. The workshop will also cover smooth, nonlinear interaction terms via the ti() and te() functions.

By the end of this session, participants should be able to fit HGAMs with smooth interaction terms, plot and interpret the models.

Fitting Models to Data Not Data to Models— Eight Workshop Series

You might have heard someone say that “all models are wrong, but some are useful”. The best way to ensure models are useful is to choose a model that is appropriate to your data and research questions, rather than forcing your data to fit your model’s assumptions (e.g., normality, independence, constant variance).

This series introduces early-career researchers to statistical models that extend beyond linear models (i.e., ANOVAs) so that they may learn how to fit models to their data rather than fitting their data to models. All workshops will use R and RStudio, so some experience with R or other programming languages is encouraged but not required. See the R Fundamentals for Data Analysis for an introduction to R and RStudio. Attendees who do not have experience with R are encouraged to review this content or take the introductory workshop concurrently if it’s being offered.

Register for individual workshops

Register for all workshops in the series

For a complete list of upcoming CSC Workshops, please visit our workshops page.

This workshop qualifies for the Scholarly Research, Writing, and Publishing Credential offered through the College of Graduate Studies.

Questions? Contact the Centre for Scholarly Communication at csc.ok@ubc.ca.