ONLINE COURSE – Path Analysis, Structural Equations and Causal Inference for Biologists (PSCB03)
https://www.prstats.org/course/path-analysis-structural-equations-and-causal-inference-for-biologists-pscb03/ 20th -24th and 27th - 30th October 2025 (9 days, approx 35 hours in total) Instructor - Prof. Bill Shipley This course, based primarily on my 2016 book <https://www.amazon.co.uk/Cause-Correlation-Biology-Structural-Equations/dp/0521529212>, teaches you how to use path analysis and structural equations modelling to test causal hypotheses using observational data that is typical of research in ecology and evolution. It is taught in half-day sessions so that you can practice individually after each half-day session. You will learn how to conduct these tests, why (and when) they are justified, and how to interpret the results. The first few lectures will primarily present the theory but practical sessions will become more prominent later in the course. The practical work will be based on R and RStudio. Students will receive R script, datasets, and a list of R packages to install. It is highly recommended that each student have a copy of my 2016 book for the course, but not essential. By the end of the course, participants should be able to: Understand the logical relationships between d-separation, data, and causal hypotheses. Know when to use piecewise SEM, when to use covariance- based SEM, and the advantages/disadvantages and assumptions of each Be able to construct, test, and interpret measurement models involving latent variables Be able to construct and identify equivalent models Be able to incorporate nested or mixed models, multigroup models, and non-normal distributions into SEM Participants are encouraged to bring their own data, as there will be opportunities throughout the course to plan, analyze, and receive feedback on structural equation models. Please 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
