permu.test

A formula of the following form: `outcome ~ predictors | timepoint variables'. Multivariate outcomes (e.g. 32 EEG electrodes) are supported; use `cbind(Fp1,Fp2,etc) ~ predictors | timepoint'.

formula

The dataset referencing these predictors.

data

If specified, will only analyze the specified subset of the data.

subset

Whether to parallelize the permutation testing using plyr's `parallel' option. Needs some additional set-up; see the plyr documentation.

parallel

A plyr `.progress' bar name, see the plyr documentation. Ignored if parallel=TRUE.

progress

Other arguments to be passed to `aovp'.

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 effects begins and ends, and the results can be plotted in various
types of heatmap for reporting.

permu.test: Permutation tests for time series data.

Description

Usage

Arguments

Value