jlmerclusterperm: Cluster-Based Permutation Analysis for Densely Sampled Time Data

An implementation of fast cluster-based permutation analysis (CPA) for densely-sampled time data developed in Maris & Oostenveld, 2007 doi:10.1016/j.jneumeth.2007.03.024 . Supports (generalized, mixed-effects) regression models for the calculation of timewise statistics. Provides both a wholesale and a piecemeal interface to the CPA procedure with an emphasis on interpretability and diagnostics. Integrates 'Julia' libraries 'MixedModels.jl' and 'GLM.jl' for performance improvements, with additional functionalities for interfacing with 'Julia' from 'R' powered by the 'JuliaConnectoR' package.

See also

Useful links:

• https://github.com/yjunechoe/jlmerclusterperm

• https://yjunechoe.github.io/jlmerclusterperm/

• Report bugs at https://github.com/yjunechoe/jlmerclusterperm/issues

Author

Maintainer: June Choe jchoe001@gmail.com (ORCID) [copyright holder]