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. Key words: Revusky’s Rn test, Type I error, Monte Carlo simulation, Autocorrelation, Serial dependency, Single-subject designs or N=1 designs.