Estimating Moments in Linear Mixed Models

In this article, we investigate estimating moments, up to fourth order, in linear mixed models. For this estimation, we only assume the existence of moments. The obtained estimators of the model parameters and the third and fourth moments of the errors and random effects are proved to be consistent or asymptotically normal. The estimation provides a base for further statistical inference such as confidence region construction and hypothesis testing for the parameters of interest. Moreover, the method is readily extended to estimate higher moments. A simulation is carried out to examine the performance of this estimating method.