The R Journal: article published in 2010, volume 2:1

MCMC for Generalized Linear Mixed Models with glmmBUGS
Patrick Brown and Lutong Zhou , The R Journal (2010) 2:1, pages 13-17.

The glmmBUGS package is a bridging tool between Generalized Linear Mixed Models (GLMMs) in R and the BUGS language. It provides a simple way of performing Bayesian inference using Markov Chain Monte Carlo (MCMC) methods, taking a model formula and data frame in R and writing a BUGS model file, data file, and initial values files. Functions are provided to reformat and summarize the BUGS results. A key aim of the package is to provide files and objects that can be modified prior to calling BUGS, giving users a platform for customizing and extending the models to accommodate a wide variety of analyses.

@article{RJ-2010-003,
  author = {Patrick Brown and Lutong Zhou},
  title = {{MCMC for Generalized Linear Mixed Models with glmmBUGS}},
  year = {2010},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2010-003},
  url = {https://doi.org/10.32614/RJ-2010-003},
  pages = {13--17},
  volume = {2},
  number = {1}
}