Abstract
We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.
Acknowledgements
We are grateful to Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundaço de Amparo à Pesquisa do Estado de So Paulo (FAPESP), Brazil for partial financial support. We also thank three anonymous referees for their careful and constructive review.