Create a heatmap of the results of permutation testing.
# S3 method for permutes
plot(x, type = c("F", "p", "w2"), breaks = NULL, ...)Output of permu.test. You may want to subset it if you want to simulate zooming in.
The quantity to plot; one of 'F' (default), 'p', or 'w2' (omega squared).
The granularity of the labels of the x axis. Pass `unique(data[,2])' to get a tick for every timepoint. Combine this trick with subsetting of your dataset, and perhaps averaging over all your dependent variables, to `zoom in' on your data to help you determine precisely where significance begins and stops to occur.
Other arguments, which will be ignored (the ellipsis is provided for consistency with the generic plot() method).
A ggplot2 object containing a heatmap of p-values.