Contents
Nonlinear models are central to ecology (e.g. growth, species interactions, thermal responses, SDMs), yet fitting them to data often goes beyond classical GLMMs. Bayesian statistics offers a powerful solution. In this hands-on workshop, we will learn how to use brms to flexibly specify, fit, and interpret nonlinear prediction models with coding effort that barely exceeds lme4, and apply them to real ecological questions.
General knowledge of statistical modeling is needed (ANOVA, linear regression, generalized linear models). Some experience with Bayesian statistics is helpful, but not required.
Lecturer
Dr Benjamin Rosenbaum
Benjamin is a Computational Ecologist with a PhD in Applied Mathematics.
His research focuses on species interactions and population & community dynamics, using both theory-driven simulation and data-driven statistical modeling. He has extensive experience in analyzing ecological data and has contributed to a wide range of biodiversity-related projects across iDiv. In his role as Statistics Support, he provides statistical consulting and courses for the entire iDiv community.