Hierarchical Statistical Models and a Generalized Likelihood Ratio Test

SUMMARY This paper deals with statistical inference for statistical models which have a nested structure. The emphasis here is on the use of a classical test of significance and on a confidence set construction approach for model identification, and the paper proposes a generalized likelihood ratio test with equal marginal error rate as a basic tool. The power performance of this test is characterized and some applications are illustrated.