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Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed

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  • Nadia Solaro
  • Pier Ferrari

Abstract

In this paper we examine maximum likelihood estimation procedures in multilevel models for two level nesting structures. Usually, for fixed effects and variance components estimation, level-one error terms and random effects are assumed to be normally distributed. Nevertheless, in some circumstances this assumption might not be realistic, especially as concerns random effects. Thus we assume for random effects the family of multivariate exponential power distributions (MEP); subsequently, by means of Monte Carlo simulation procedures, we study robustness of maximum likelihood estimators under normal assumption when, actually, random effects are MEP distributed.
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  • Nadia Solaro & Pier Ferrari, 2007. "Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(1), pages 51-67, June.
  • Handle: RePEc:spr:stmapp:v:16:y:2007:i:1:p:51-67
    DOI: 10.1007/s10260-006-0016-6
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    1. Lindsey, J. K., 1999. "Models for Repeated Measurements," OUP Catalogue, Oxford University Press, edition 2, number 9780198505594.
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