A Monte Carlo study of the Friedman and Conover tests tn the single-factor repeated measures design
A Monte Carlo study was used to compare the Type I error rates and power of two nonparametric tests against the F test for the single-factor repeated measures model. The performance of the nonparametric Friedman and Conover tests was investigated for different distributions, numbers of blocks, and numbers of repeated measures. The results indicated that the type of the distribution has little effect on the ability of the Friedman and Conover tests to control Type I error rates. For power, the Friedman and Conover tests tended to agree in rejecting the same false hypothesis when the design consisted of three repeated measures. However, the Conover test was more powerful than the Friedman test when the number of repeated measures was 4 or 5. Still, the F test is recommended for the single-factor repeated measures model because of its robustness to non-normality and its good power across a range of conditions.
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