A Student's Guide to Randomization Statistics for Multichannel Event-Related Potentials Using Ragu - Habermann, Marie; Weusmann, Dorothea; Stein, Maria; Koenig, Thomas (Frontiers in Neuroscience, 2018)
In this paper we present an multivariate approach to analyze multi-channel ERP data using randomization statistics \footnotemark[1]. The MATLAB-based open source toolbox Randomization Graphical User interface (Ragu) provides among other things a test for topographic consistency, topographic analysis of variance, t-mapping and microstates analysis. Up to two within-subject factors and one between-subject factor can be defined and analyzed in Ragu. Ragu includes all sensor signals and no a-priori models have to be applied. Also, periods of significant effects can be controlled for multiple testing using global overall statistics over time. Here we introduce the different options of Ragu by a step by step analysis of data from an example study examining the neural reaction of semantic unexpected sentence endings in exchange students at the beginning and after 5 months of a stay in a foreign-language country.