Randomization Test

A randomization test (also called a permutation test) is a non-parametric statistical test that computes a p-value by re-shuffling the observed data many times under the null hypothesis and asking how often the re-shuffled data produce a test statistic as extreme as the one actually observed. Because it makes no assumptions about the underlying distribution, it is particularly well-suited to small samples, single-subject designs, and ordinal outcome data — all common in accessibility research, where recruiting large numbers of participants with a specific disability profile is hard. Todman and Dugard's textbook provides practical software for applying randomization tests to ABA-reversal and other single-case experimental designs.