Articles
Topics
- Tidying output
Collecting {jlmerclusterperm} objects as tidy data frames
- Julia interface
Interacting with Julia regression models from R using {JuliaConnectoR}
- Reproducibility
Using RNG seed and counter state to guarantee reproducibility of results
- Asynchronous CPA
Using {future} to run CPA asynchronously in a background process
- Comparison to eyetrackingR
Translating eyetrackingR code for CPA with jlmerclusterperm
Case Studies
- Garrison et al. 2020
A walkthrough of basic package features and the components of a CPA
- Geller et al. 2020
A walkthrough of t vs. chisq statistic in a (mixed-effects) CPA
- de Carvalho et al. 2021
A walkthrough of multi-level contrasts and model complexity in a CPA
- Ito et al. 2018
Interpreting main effects and interaction effects in a CPA