Failure to recognize the serious implications of heterogeneous correlations and disregard of the multiple test problem in interpreting the results from repeated measurements ANOVA of any single primary outcome measure can produce false-positive error rates that are more than five times the alpha level that is reported. Alternative analyses that do not depend on the symmetry assumption, together with a Bonferroni correction of the multiple tests of significance that are routinely accomplished by the repeated measurements ANOVA, appropriately control the probability of statistical support for a false-positive claim. The magnitudes of error inflation and appropriate procedures for error control are examined in this article using simulated clinical trials data.