Bayesian Multilevel Models for Repeated Measures Data: A Conceptual and Practical Introduction in R

This comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language. Featuring a series of fully worked analyses of repeated-measures data, focus is placed on active learning through the analyses of the progressively more complicated models presented throughout the book.

Santiago Barreda is a phonetician in the Linguistics department at the University of California, Davis, USA, with a particular interest in speech perception.

Noah Silbert is a former Academic and is currently a practicing Stoic. His training and background are in phonetics, perceptual modeling, and statistics.