The effect of imbalance on significance- testing in one- way model ii analysis of variance

Abstract
The effect of imbalance on two methods of testing hypotheses about the between-group variance component in a one-way random effects model is investigated over a wide range of designs. For testing non-zero values of it is found that the likelihood A ratio statistic is rarely preferable to the F-statistic, even for substantial amounts of extremely imbalanced data. However the likelihood ratio statistic can be appreciably more powerful than the F-statistic in testing for a null value of if the data is extremely imbalanced.