brms workshop

Author

Affiliation

Matti Vuorre

Tilburg University

Plan

We plan to tackle some or all of the topics below:

Collaboration and workflow
Multilevel models: Priors, outcome distributions, and model comparison
Ordinal models
Signal Detection Theoretic models
Censored models

Our plan is to walk through (some of) them, and edit the code to address your questions.

Materials

The materials of this workshop are organized in Quarto files. The source code is on GitHub.

Prerequisites

We assume some familiarity with basic statistical modeling and the R language. If you’d like a refresher, see Introduction to Modern Statistics & R for Data Science. To follow along, you need to have

R (https://cran.r-project.org/)
An R IDE like RStudio (recommended for beginners) or Positron (advanced)
Quarto (for rendering the materials into a website)
Git
A GitHub account (if you want to participate in live troubleshooting / contributing)

Build / reproduce

Note that building the project will run all the analysis documents, which involve bayesian models: This will take a long time. Because of this, you should first create an .Renviron file to describe your system settings (see .Renviron.example). For example,

echo "
MAX_CORES = 8
BRMS_BACKEND = "cmdstanr"
BRMS_THREADS = 2
BRMS_ITER = 1000
" >> .Renviron

Then, to recreate the materials locally, run the following in your terminal, not R (requires GNU Make). This will download the workshop materials (all source code), and then run the required code.

git clone https://github.com/mvuorre/workshop.git
cd brms-workshop.git
make

If you do not have Make installed (i.e. you are on Windows), you need to execute the steps to build (or reproduce) manually. See Makefile.

Contribute

Issues & pull requests at https://github.com/mvuorre/workshop are welcome.