What and why

This ebook is based on the second edition of Richard McElreath’s (2020a) text, Statistical rethinking: A Bayesian course with examples in R and Stan. My contributions show how to fit the models he covered with Paul Bürkner’s brms package (Bürkner, 2017, 2018, 2020f), which makes it easy to fit Bayesian regression models in R (R Core Team, 2020) using Hamiltonian Monte Carlo. I also prefer plotting and data wrangling with the packages from the tidyverse (Wickham, 2019; Wickham et al., 2019). So we’ll be using those methods, too.

Caution: Work in progress

The inaugural 0.0.1 release contained first drafts of Chapters 1 through 9. The 0.0.2 update adds drafts of Chapters 10 thorugh 12, which give a fine introduction to the generalized linear model.

There is no timetable for this project, but I’ll update it periodically with new chapters and so on. To keep up with the latest changes, check in at the GitHub repository, https://github.com/ASKurz/Statistical_Rethinking_with_brms_ggplot2_and_the_tidyverse_2_ed, or follow my announcements on twitter at https://twitter.com/SolomonKurz.

Thank-you’s are in order

Before we move on, I’d like to thank the following for their helpful contributions:

References

Bürkner, P.-C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80(1), 1–28. https://doi.org/10.18637/jss.v080.i01

Bürkner, P.-C. (2018). Advanced Bayesian multilevel modeling with the R package brms. The R Journal, 10(1), 395–411. https://doi.org/10.32614/RJ-2018-017

Bürkner, P.-C. (2020f). brms: Bayesian regression models using ’Stan’. https://CRAN.R-project.org/package=brms

McElreath, R. (2020a). Statistical rethinking: A Bayesian course with examples in R and Stan (Second edition). CRC Press. https://xcelab.net/rm/statistical-rethinking/

R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/

Wickham, H. (2019). tidyverse: Easily install and load the ’tidyverse’. https://CRAN.R-project.org/package=tidyverse

Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686