*FREE – Introduction to Generalised Linear Mixed Models for Ecologists (FMME01)*
https://www.prstats.org/course/free-introduction-to-generalised-linear-mixed-models-for-ecologists-fmme01/ *Free, one-day live online course — August 14, 2025* ------------------------------ *Course Overview* This 4-hour online workshop offers a practical and accessible introduction to Generalised Linear Mixed Models (GLMMs) using R. It builds on the principles of GLMs by incorporating random effects, making it ideal for analysing data with hierarchical or grouped structures. The session will combine clear explanations of theory with hands-on coding in R, helping participants understand when and why GLMMs are used, and how to interpret them confidently. ------------------------------ *Topics Covered* - Key theoretical foundations of GLMMs and when to use them - Understanding fixed vs. random effects - Selecting appropriate error distributions and link functions - Fitting GLMMs in R using lme4 and related packages - Model selection, checking assumptions, and interpreting results - Applying GLMMs to real ecological datasets ------------------------------ *Technical Requirements* - Installation of R and RStudio before the session (free and compatible with Windows, macOS, and Linux) - Webcam recommended for interactive engagement - Multi-monitor setup optional but helpful for working through exercises while viewing materials ------------------------------ *Intended Audience* This course is designed for ecologists, postgraduate researchers, early-career data analysts, and anyone with a basic understanding of R and GLMs. It is particularly suited to those analysing data with repeated measures, nested designs, or other hierarchical structures. Prior experience with GLMs is recommended, but not essential. ------------------------------ *Cost & Registration* Free of charge — secure your place via PR Statistics’ site. Spaces are limited and allocated on a first-come, first-served basis. ------------------------------ *Join us for this free introduction to GLMMs and learn how to handle complex, grouped, and non-independent data confidently using R. Register early to avoid missing out!* We recently started refreshing our social media and would really appreciate your support. If you’re active on any of the platforms below, please follow us and engage with any posts that catch your interest — a quick like or share can go a long way in helping us build momentum. We’ll be posting regular course updates, plus running competitions and giveaways. *To kick things off, we’re offering £500 in course credit to one randomly selected follower on each platform — that’s £2,000 in total! The more platforms you follow and posts you like or share, the better your chances of winning.* You can find us here: *BlueSky* | @prstats.bsky.social <https://bsky.app/profile/prstats.bsky.social> *X (Twitter)* | @pr_stats <https://twitter.com/pr_stats> *Mastodon* | @prstats <https://mastodon.social/@prstats> *Instagram* | @pr._.stats <https://instagram.com/pr._.stats> We’re also setting up our *Facebook* page. If you follow us now, you’ll be automatically entered into the giveaway once we go live: *Facebook* | PR stats <https://www.facebook.com/profile.php?id=61576148023294> Thanks in advance for your support, *Oliver* -- Oliver Hooker PhD. PR stats [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
