Type I error rate and power for the t test, Wilcoxon-Mann-Whitney (U)
test, van der Waerden Normal Scores (NS) test, and Welch-Aspin-Sattert
hwaite (W) test were compared for two independent random samples drawn
from nonnormal distributions. Data with varying degrees of skewness (
S) and kurtosis (K) were generated using Fleishman's (1978) power func
tion. Five sample size combinations were used with both equal and uneq
ual variances. For nonnormal data with equal variances, the power of t
he U test exceeded the power of the t test regardless of sample size.
When the sample sizes were equal but the variances were unequal, the t
test proved to be the most powerful test. When variances and sample s
izes were unequal, the W test became the test of choice because it was
the only test that maintained its nominal Type I error rate.