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

This book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language, with a focus on active learning through the analyses of progressively more complicated models. It offers code, examples, and an accessible approach for readers with any statistical background.

Format: Hardback
Length: 460 pages
Publication date: 02 May 2023
Publisher: Taylor & Francis Ltd

This comprehensive book serves as an introductory guide to multilevel Bayesian models in R and the Stan programming language. With a focus on active learning through the analysis of progressively complex models, it presents a series of fully worked analyses of repeated measures data.

Beginning with simple two-group comparisons and progressing to multinomial regression models with numerous random effects, the book covers a wide range of statistical topics. Spanning 13 well-organized chapters, readers are provided with all the code required to execute all the analyses and create all the plots presented throughout the book. Additionally, useful examples are provided to aid in interpreting and reporting the results of their own analyses.

Designed to be accessible to readers from various fields and with varying statistical backgrounds, this book is an ideal resource for senior undergraduate students, graduate students, and experienced researchers seeking to transition their skills from traditional models to a Bayesian framework. Its comprehensive coverage and practical approach make it a valuable tool for those looking to expand their knowledge in this area.

Weight: 1060g
Dimension: 246 x 174 (mm)
ISBN-13: 9781032259628