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) . 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) .