Dear all, We are excited to announce the 4th edition of our Generalized Linear Mixed Models (GLMMs) in R online course, taking place September 21–24.. For more information and to register, please visit: [ https://www.physalia-courses.org/courses-work/glmms-in-r ]( https://www.physalia-courses.org/courses-work/glmms-in-r ) This course is designed for graduate students and researchers with experience in generalized linear models who want to deepen their skills to analyze complex grouped and correlated data. You will learn to specify, interpret, and validate GLMMs using the R packages lme4 and glmmTMB, along with hands-on training on model diagnostics and assumption checking using DHARMa. The basics of linear models (LM), generalized linear models (GLM), and ANOVA are reviewed at the start of the course. However, if you do not have a solid understanding of these topics, you may benefit more from our course “Generalized Linear Models as a Unified Framework for Data Analysis in R,” also offered by Physalia: [ https://www.physalia-courses.org/courses-workshops/glm-in-r-1/ ]( https://www.physalia-courses.org/courses-workshops/glm-in-r-1/ ) Best regards, Carlo
-------------------- Carlo Pecoraro, Ph.D Physalia-courses DIRECTOR [email protected] mobile: +49 17645230846 [ Bluesky ]( https://bsky.app/profile/physaliacourses.bsky.social ) [ Linkedin ]( https://www.linkedin.com/in/physalia-courses-a64418127/ ) [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
