Bayesian Profile Regression using Generalised Linear Mixed Models R package ProfileGLMM version 1.1.0 Implements a Bayesian profile regression using a generalized linear mixed model as output model. The package allows for binary (probit mixed model) and continuous (linear mixed model) outcomes and both continuous and categorical clustering variables. The package utilizes 'RcppArmadillo' and 'RcppDist' for high-performance statistical computing in C++. For more details see Amestoy & al. (2025) <doi:10.48550/arXiv.2510.08304>. Software Depends: R (>= 3.5) Imports: Rcpp, LaplacesDemon, MCMCpack, Matrix, Spectrum, mvtnorm LinkingTo: Rcpp, RcppArmadillo, RcppDist Suggests: knitr, rmarkdown Matteo Amestoy <m.amestoy@amsterdamumc.nl> Comprehensive R Archive Network (CRAN) Matteo Amestoy [aut, cre, cph], Mark van de Wiel [ths], Wessel van Wieringen [ths] GPL-2 2026-02-03 application/tgz https://CRAN.R-project.org/package=ProfileGLMM doi:10.32614/CRAN.package.ProfileGLMM