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Robustness of parameter estimation procedures in multilevel models when random effects are MEP distributed. (English) Zbl 1157.62034

Summary: 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 the normality assumption when, actually, random effects are MEP distributed.

MSC:

62H12 Estimation in multivariate analysis
62F35 Robustness and adaptive procedures (parametric inference)
65C05 Monte Carlo methods

Software:

MEMSS; S-PLUS
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References:

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