Uses computer simulation to study the effects on parametric and nonparametric statistical tests when assumptions of normality and homogeneity of variance are violated. Results reveal that nonparametric methods are not always acceptable substitutes for parametric methods in research studies when parametric assumptions are not satisfied. (SLD)

The power functions of Student t tests performed on initial scores, ordinary ranks, 3 kinds of modular ranks, and dichotomies were investigated for 1 normal and 3 nonnormal distributions using 2 samples of 26 simulated scores each. Advantages of extending the rank transformation concept are discussed. (SLD)

It is argued that outlier-prone distributions reduce the power of nonparametric tests, but power can be restored through procedures usually associated with parametric tests. Computer simulation is used to show how an outlier detection and downweighting procedure augments the power of the t-test and the Wilcoxon-Mann-Whitney test. (SLD)

Coefficient alpha was examined through computer simulation as an estimate of test reliability under violation of two assumptions. Coefficient alpha underestimated reliability under violation of the assumption of essential tau-equivalence of subtest scores and overestimated it under violation of the assumption of uncorrelated subtest error scores.…

A modified "F" test is derived that includes a correction for nonindependence of between-groups and within-groups sample values in analysis of variance (ANOVA) designs. Computer simulations based on normal and nonnormal distributions illustrate the usefulness of the approach, which was more powerful than conventional within-subjects…

Comparisons of the Wilcoxon test, Friedman test, and repeated-measures analysis of variance (ANOVA) on ranks in a computer simulation show that the Friedman test performs like the sign test whereas the ANOVA performs like the Wilcoxon test. Classification of these tests in introductory statistics textbooks should be revised. (SLD)