Package: permutes 2.7

Cesko C. Voeten

permutes: Permutation Tests for Time Series Data

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>.

Authors:Cesko C. Voeten [aut, cre]

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permutes.pdf |permutes.html✨
permutes/json (API)

# Install 'permutes' in R:
install.packages('permutes', repos = c('https://cvoeten.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://gitlab.com/cvoeten/permutes

Datasets:
  • MMN - ERP data from Jager (in prep.). See the vignettes for details.

On CRAN:

4.11 score 13 scripts 874 downloads 11 exports 2 dependencies

Last updated 1 years agofrom:30ff049a8c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-winOKNov 10 2024
R-4.5-linuxOKNov 10 2024
R-4.4-winOKNov 10 2024
R-4.4-macOKNov 10 2024
R-4.3-winOKNov 10 2024
R-4.3-macOKNov 10 2024

Exports:clusterperm.glmclusterperm.glmerclusterperm.glmmTMBclusterperm.lmclusterperm.lmerperm.glmperm.glmerperm.glmmTMBperm.lmperm.lmerpermu.test

Dependencies:plyrRcpp

Analyzing time series data using clusterperm.lmer

Cesko C. Voeten

Rendered frombuildmer.Rmdusingknitr::rmarkdownon Nov 10 2024.

Last update: 2023-09-11
Started: 2021-02-22

Analyzing time series data using permu.test

Cesko C. Voeten

Rendered frompermutes.Rmdusingknitr::rmarkdownon Nov 10 2024.

Last update: 2021-09-14
Started: 2017-09-21

Readme and manuals

Help Manual

Help pageTopics
Cluster-based permutation tests for time series data, based on generalized linear models or other 'buildmer' models. This is an alias for 'clusterperm.lm' provided for discoverability.clusterperm.glm
Cluster-based permutation tests for time series data, based on generalized linear mixed-effects models or other 'buildmer' models. This is an alias for 'clusterperm.lmer' provided for discoverability.clusterperm.glmer
Cluster-based permutation tests for time series data, based on 'buildglmmTMB'.clusterperm.glmmTMB
Cluster-based permutation tests for time series data, based on mixed-effects models or other 'buildmer' models. This is an alias for 'clusterperm.lmer', except that random effects are explicily disallowed.clusterperm.lm
Cluster-based permutation tests for time series data, based on mixed-effects models or other 'buildmer' models.clusterperm.lmer
ERP data from Jager (in prep.). See the vignettes for details.MMN
A general permutation test for mixed-effects models or other 'buildmer' models. This is an alias for 'perm.lm' provided for discoverability.perm.glm
A general permutation test for mixed-effects models or other 'buildmer' models. This is an alias for 'perm.lmer' provided for discoverability.perm.glmer
A general permutation test for 'glmmTMB' models.perm.glmmTMB
A general permutation test for mixed-effects models or other 'buildmer' models. This is an alias for 'perm.lmer', except that random effects are explicily disallowed.perm.lm
A general permutation test for mixed-effects models or other 'buildmer' models.perm.lmer
Permutation tests for time series data, based on classic linear regression or ANOVA This is a legacy function that is primarily provided for backward compatibility. You should probably use 'perm.lm' or 'perm.lmer' instead. 'permu.test' is the only function to support multivariate responses, although multivariate data can trivially be recoded into a univariate model. 'permu.test' does not support random effects or corrected p-values (e.g. the cluster mass test), which are supported by 'permutelm'.permu.test
Create a heatmap of the results of cluster-based permutation testing.plot.permutes