We are thrilled to announce our upcoming course on "Generalized Additive Models in R: A Data-Driven Approach to Estimating Regression Models," scheduled to take place from November 20th to 24th, 2023. With a commitment to fostering international participation, this course will be offered online, allowing you to join from anywhere in the world.
Course website: https://www.physalia-courses.org/courses-workshops/gams-in-r/
Are you ready to delve into the world of statistical analysis with a fresh perspective? Generalized Additive Models (GAMs) offer a powerful alternative to traditional fixed functional forms, enabling you to learn relationships between covariates and responses directly from the data using splines. In this immersive five-day course, we will guide you through the practical application of GAMs using the mgcv and brms packages in R. By the end of the course, you will not only understand the inner workings of GAMs but also gain the skills to leverage them effectively in your analyses.
Target Audience and Assumed Background:
Designed for graduate students and researchers with a foundation in statistical knowledge, this course is ideal for those familiar with generalized linear models, likelihood, and AIC. Don't worry if your expertise in these areas is a bit rusty – we'll recap the essentials. While prior knowledge of mixed effects or hierarchical models is beneficial, it is not a prerequisite. Participants should be comfortable with RStudio and possess a degree of fluency in programming R code, including data importation, manipulation, and visualization.
By the end of the course, participants will be equipped with the following skills:
- Understand the practical implementation of GAMs to learn relationships from data
- Fit GAMs using R's mgcv and brms packages
- Differentiate between types of splines and select the appropriate ones for your models
- Visualize fitted GAMs and assess model assumptions
For more information about our courses, please have a look at: https://www.physalia-courses.org/courses-workshops