Boehnke, Klaus2019-01-082019-01-0819840013-1644https://depositonce.tu-berlin.de/handle/11303/8833http://dx.doi.org/10.14279/depositonce-7962Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The effects of some restraints not included in the classical assumptions of the F- and H-test (e.g., correlation of mean and sample size) were examined in a simulation design of 1000 samples per condition. Also simulated was a situation in which two assumptions were not met simultaneously. The major conclusions were: H was not an appropriate alternative for F with samples of N>= 20; in all cases of unequal variances combined with unequal sample sizes H should be applied; and neither H nor F should be applied if more than one assumption of either test is not met.en370 Bildung und Erziehung150 PsychologieH-testF-teststatisticsrobustnessparametric testnon-parametric testmethodologyArticle1552-3888