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13.334 Articles in journals published by the UPC
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Likelihood for random-effect models (invited article)

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Lee, Youngjo
Nelder, J. A.
Document typeArticle
Defense date2005
PublisherInstitut d'Estadística de Catalunya
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 2.5 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 2.5 Spain
Abstract
HolaFor inferences from random-effect models Lee and Nelder (1996) proposed to use hierarchical likelihood (h-likelihood). It allows inference from models that may include both fixed and random parameters. Because of the presence of unobserved random variables h-likelihood is not a likelihood in the Fisherian sense. The Fisher likelihood framework has advantages such as generality of application, statistical and computational efficiency. We introduce an extended likelihood framework and discuss why it is a proper extension, maintaining the advantages of the original likelihood framework. The new framework allows likelihood inferences to be drawn for a much wider class of models.
CitationLee, Youngjo; Nelder, J. A.. "Likelihood for random-effect models (invited article)". SORT, 2005, Vol. 29, núm. 2 
URIhttp://hdl.handle.net/2099/3768
ISSN1696-2281
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  • SORT (Statistics and Operations Research Transactions) - 2005, Vol. 29, Núm. 2 [8]
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