It was proposed that the data from Monte Carlo statistical investigations be subjected to analysis of variance methods rather than the conventional techniques of tabling, graphing, and inspecting the data. Two examples in which analysis of variance methods were applied to published Monte Carlo studies were presented. It was suggested that balanced factorial designs should be used whenever possible in Monte Carlo studies so that analysis of variance methods would be directly applicable. Finally, three advantages of analysis of variance methods (...) over conventional techniques were described and analysis of variance methods were contrasted with a possible alternative analytical method, multiple regression analysis. (shrink)

Robustness properties of three equality of variances tests, the jackknife procedure, the k-sample Box-Andersen test, and Levene’s z test, were investigated and compared in a Monte Carlo study employing small samples from underlying gamma distributions and gamma mixtures. Overall, the jackknife test yielded rejection proportions usually closer to nominal levels under departures from normality, but the Box-Andersen test performed relatively well when departures from normality were not extreme. Four recommendations regarding testing variances were offered.