In addition to my research, I develop open source software. The package I work on wraps cognitive measurement models in a brms-compatible interface, so fitting them feels more like running a regression than writing a custom sampler. Below you can find an overview of my open source software contributions.
bmm
bmm is an R package I co-develop with Ven Popov for fitting cognitive measurement models in a hierarchical Bayesian framework. It builds on brms and Stan, and uses the same formula syntax. If you know brms, you already know most of how bmm works.
The current focus is measurement models for working memory. bmm implements different measurement models all in one place, providing a flexible and user-friendly interface for Bayesian hierarchical mixture models and related cognitive measurement models.
Install
# From CRAN
install.packages("bmm")
# Development version
remotes::install_github("venpopov/bmm")Selected References
- Frischkorn, G. T., & Popov, V. (2025). A tutorial for estimating Bayesian hierarchical mixture models for visual working memory tasks: Introducing the Bayesian Measurement Modeling (bmm) package for R. Behavior Research Methods, 57(5), 144. https://doi.org/10.3758/s13428-025-02643-0