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