Autocorrelation effect on type I error rate of Revusky’s Rn test: A Monte Carlo study

Monte Carlo simulation was used to determine how violation of the
independence assumption affects the empirical probability distribution and
Type I error rates of Revusky's Rn statistical test. Simulation results show that
the probability distribution of Rn was distorted when the data were
autocorrelated. A corrected Rn statistic was proposed to reach a reasonable fit
between theoretical (exact) and empirical Type I error rates. We recommend
using the corrected Rn statistic when serial dependence in the data is
suspected.