Helps you determine the analysis window to use when analyzing densely-sampled time-series data, such as EEG data, using permutation testing (Maris & Oostenveld, 2007) <doi:10.1016/j.jneumeth.2007.03.024>. These permutation tests can help identify the timepoints where significance of an effect begins and ends, and the results can be plotted in various types of heatmap for reporting. Mixed-effects models are supported using an implementation of the approach by Lee & Braun (2012) <doi:10.1111/j.1541-0420.2011.01675.x>.
| Version: | 2.6 |
| Depends: | R (≥ 2.10) |
| Imports: | plyr, stats, utils |
| Suggests: | buildmer (≥ 2.3), car, doParallel, ggplot2, glmmTMB, knitr, lme4, lmPerm, permuco, rmarkdown, viridis |
| Published: | 2022-07-13 |
| Author: | Cesko C. Voeten [aut, cre] |
| Maintainer: | Cesko C. Voeten <cvoeten at gmail.com> |
| BugReports: | https://github.com/cvoeten/permutes/issues |
| License: | FreeBSD |
| NeedsCompilation: | no |
| CRAN checks: | permutes results |
| Reference manual: | permutes.pdf |
| Vignettes: |
Analyzing time series data using 'clusterperm.lmer' Analyzing time series data using 'permu.test' |
| Package source: | permutes_2.6.tar.gz |
| Windows binaries: | r-devel: permutes_2.6.zip, r-release: permutes_2.6.zip, r-oldrel: permutes_2.6.zip |
| macOS binaries: | r-release (arm64): permutes_2.6.tgz, r-oldrel (arm64): permutes_2.6.tgz, r-release (x86_64): permutes_2.6.tgz, r-oldrel (x86_64): permutes_2.6.tgz |
| Old sources: | permutes archive |
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