brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
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Updated
Jun 6, 2024 - R
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
Bayesian analysis + tidy data + geoms (R package)
Covers the basics of mixed models, mostly using @lme4
Workshop on using Mixed Models with R
👓 Functions related to R visualizations
Helper functions for brmsfit objects (DEPRECATED)
Workshop to introduce participants to rstanarm and brms.
An R package for extracting results from mixed models that are easy to use and viable for presentation.
R package to run Bayesian MMRMs using {brms}
Population-level infectious disease modelling as an extension of brms.
Materials for a 3 to 4 hour workshop on Bayesian Statistics using the R package `brms`
Complementary repository with data and code for Wolf & Tollefsen, 2021.
A quick reference for how to run many models in R.
R package 'faintr' for interpretation of BRMS model fits for data from factorial design experiment
Workshop materials for learnB4SS
This incomplete repository is used to facilitate the consultation of individual files in this project. Only files smaller than 100 MB are available here. The complete project is available at https://doi.org/10.17605/OSF.IO/GT5UF.
Demonstration of alternatives to lme4
An R package providing a GUI ('shiny' app) for the R package 'brms'.
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