Constraints on Random Effects and Mixed Linear Model Predictions

In Mixed Linear Models theory one is assumed to know the structure of random effects covariance matrix. The suggestions are sometimes contradictious, especially if the model includes interactions between fixed effects and random effects. This paper presents conditions under which two different random effects' variance matrices will yield equal estimation and prediction results. Some examples and simulation results are given also.