An Introduction to Bayesian Multilevel Modeling with brms

In this talk, Professor Paul Bürkner provides an introduction to Bayesian multilevel modeling with the R package brms. It is powered by the probabilistic programming language Stan and supports a wide range of response distributions and advanced modeling options such as Gaussian processes, splines, autocorrelation, or censoring all in a multilevel context. Together with the available post-processing and plotting methods, brms can be used for end-to-end data analysis following a principled Bayesian workflow. Speakers Professor Paul Bürkner Paul is a statistician with a focus on probabilistic (Bayesian) methods currently working as a Full Professor of Computational Statistics at TU Dortmund University, Department of Statistics. Having originally studied psychology and mathematics, his core research is nowadays located somewhere between statistics and machine learning, with applications in almost all quantitative sciences. Paul is also deeply involved in open-source software development. In particular, he is the author of the R package brms and member of the Stan Development Team.