ausal Inference for Ecologists (CIFE01) Causal Inference for Ecologists is an applied R course teaching researchers how to identify and estimate causal effects in ecological and environmental data.
https://prstats.org/course/causal-inference-for-ecologists-cife01/ *23–27 March 2026 - **Live Online* Do you work with ecological data and need to move beyond correlation to understand cause-and-effect? Join our five-day *Causal Inference for Ecologists* course and gain the practical tools to answer real causal questions using both experimental and observational datasets. In this course, you will learn how to: - Construct and interpret *Directed Acyclic Graphs (DAGs)* to formalise causal assumptions. - Identify and avoid bias from confounders and colliders. - Understand why traditional model selection methods like AIC can mislead causal analysis. - Apply causal inference frameworks to your own ecological research problems. Our live online format includes lectures, hands-on practical exercises, and open discussions. All sessions are recorded and made available to participants across time zones. *Who Should Attend:* Quantitative scientists with experience in R who are testing hypotheses, estimating causal effects, or building predictive models. *Software:* We will work with *lme4* and *rstanarm*, covering both frequentist and Bayesian modelling approaches. *Secure your place today and transform the way you answer causal questions in ecological research.* Register at *prstats.org/course/causal-inference-for-ecologists-cife01/ <http://prstats.org/course/causal-inference-for-ecologists-cife01/>* Email [email protected] with any questions -- 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
