Testing normality in mixed models using a transformation method

Statistical inference often assumes the normality of the variables involved in the model under study. The existing tests are for independent observations and may not be readily extended to handle the case with correlated ones. In this paper, a transformation method is recommended for normality checking in the two-way analysis of variance model. Its sampling properties are investigated. Simulation studies are carried out to examine the performance of the proposed methodology.