Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed
AbstractIn 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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Bibliographic InfoArticle provided by Springer in its journal Statistical Methods and Applications.
Volume (Year): 16 (2007)
Issue (Month): 1 (June)
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Web page: http://link.springer.de/link/service/journals/10260/index.htm
Other versions of this item:
- Nadia Solaro & Pier Alda Ferrari, 2005. "Robustness of parameter estimation procedures in multilevel models when random effects are MEP distributed," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1013, Universitá degli Studi di Milano.
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