Over the past two years, several people have blogged about my R package **brms**, which allows to fit Bayesian generalized non-linear multilevel models using Stan. This post is intended to provide links to those blog posts.

## List of blog posts

- Easily made fitted and predicted values made easy by Andrew MacDonald
- How to compute Bayes factors using lm, lmer, BayesFactor, brms, and JAGS/stan/pymc3 by Jonas Kristoffer Lindelov
- Confounded dose-response effects of treatment adherence: fitting Bayesian instrumental variable models using brms by Kristoffer Magnusson
- PK/PD reserving models by Markus Gesmann
- Hierarchical compartmental reserving models by Markus Gesmann
- Diffusion/Wiener Model Analysis with brms – Part II: Model Diagnostics and Model Fit by Henrik Singmann
- Bayesian SEM with brms by Jarrett Byrnes
- Diffusion/Wiener Model Analysis with brms – Part I: Introduction and Estimation by Henrik Singmann
- Bayesian Decision Theory Made Ridiculously Simple by Justin Silverman
- Bayesian Estimation of Signal Detection Models, Part 4 by Matti Vuorre
- Bayesian Estimation of Signal Detection Models, Part 3 by Matti Vuorre
- Bayesian Estimation of Signal Detection Models, Part 2 by Matti Vuorre
- Bayesian Estimation of Signal Detection Models, Part 1 by Matti Vuorre
- Three methods for computing the intra-class correlation in multilevel logistic regression by Ladislas Nalborczyk
- More support for Bayesian analysis in the sj!-packages #rstats #rstan #brms by Daniel Luedecke
- R packages interfacing with Stan: brms posted on Andrew Gelmans blog
- Bayesian mixed effects (aka multi-level) ordinal regression models with brms by Kevin Stadler
- Bayes factors with brms by Matti Vuorre
- How to Compare Two Groups with Robust Bayesian Estimation Using R, Stan and brms by Matti Vuorre
- Better forest plots from meta-analytic models estimated with brms by Matti Vuorre
- Meta-analysis is a special case of Bayesian multilevel modeling by Matti Vuorre
- brms continuous its streak by Wayne Folta
- brms 0.8 adds non-linear regression by Wayne Folta
- R Users Will Now Inevitably Become Bayesians by Wayne Folta
- Bayesian regression models using Stan in R by Markus Gesmann