A plea for more general tests than those for location only: Further considerations on Rasch & Guiard’s ‘The robustness of parametric statistical methods’

Starting with the discussion between Rasch & Guiard (2004) and von Eye (2004) concerning the use of parametric and nonparametric tests for the comparison of two samples a further approach toward this question is undertaken. Student’s t-test requires for its application interval scaled and normally distributed data along with homogeneous variances across groups. In case that at least one of these prerequisites is not fulfilled, common statistical textbooks for social sciences usually refer to the nonparametric Wilcoxon-Mann-Whitney test. Earlier simulation studies revealed the t-test to be rather robust concerning distributional assumptions. The current study extends these findings with respect to the simultaneous violation of distributional and homogeneity assumptions. A simulation study has shown that both tests lead to highly contradicting results, and a more general approach toward the question of whether parametric or nonparametric procedures should be used, is introduced. Results indicate that the U-Test seems to be in general a more proper instrument for psychological research.