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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