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On Parameters Estimation Procedures in Multilevel Models

Authors: Pier Alda Ferrari; Nadia Solaro;

On Parameters Estimation Procedures in Multilevel Models

Abstract

We examine maximum likelihood estimation procedures in multilevel models relatedbto two-level hierarchically structured data. Usually, for fixed effects and variance components estimation, multivariate normal distribution is assumed. Here we consider for random effects multivariate exponential power distribution (MEP), which represents one of the possible generalizations of multivariate normal distribution. We examine robustness of maximum likelihood estimators under normal assumption when, indeed, random effects are MEP distributed. The study is conducted through MC simulation procedures.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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