The effect of design imbalance on the power of the F-test of a variance component in the one-way random model

The ANOVA-based F-test used for testing the significance of the random effect variance component is a valid test for an unbalanced one-way random model. However, it does not have an uniform optimum property. For example, this test is not uniformly most powerful invariant (UMPI). In fact, there is no UMPI test in the unbalanced case (see KHURI, MATHEW, and SINHA, 1998). The power of the F-test depends not only on the design used, but also on the true values of the variance components. As KHURI (1996) noted, we can gain a better insight into the effect of data imbalance on the power of the F-test using a method for modelling the power in terms of the design parameters and the variance components. In this study, generalized linear modelling (GLM) techniques are used for this purpose. It is shown that GLM, in combination with a method of generating designs with a specified degree of imbalance, is an effective way of studying the behavior of the power of the F-test in a one-way random model.