Likelihood for random-effect models (with discussion).

Lee, Youngjo, and Nelder, John A.. "Likelihood for random-effect models (with discussion).." SORT 29.2 (2005): 141-164. <http://eudml.org/doc/40471>.

@article{Lee2005,
abstract = {For inferences from random-effect models Lee and Nelder (1996) proposed to use hierarchical likelihood (h-likelihood). It allows influence 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.},
author = {Lee, Youngjo, Nelder, John A.},
journal = {SORT},
keywords = {Modelos estadísticos; Modelo jerárquico; Estimador de máxima verosimilitud; H-verosimilitud; generalized linear models; hierarchical models; h-likelihood},
language = {eng},
number = {2},
pages = {141-164},
title = {Likelihood for random-effect models (with discussion).},
url = {http://eudml.org/doc/40471},
volume = {29},
year = {2005},
}

TY - JOUR
AU - Lee, Youngjo
AU - Nelder, John A.
TI - Likelihood for random-effect models (with discussion).
JO - SORT
PY - 2005
VL - 29
IS - 2
SP - 141
EP - 164
AB - For inferences from random-effect models Lee and Nelder (1996) proposed to use hierarchical likelihood (h-likelihood). It allows influence 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.
LA - eng
KW - Modelos estadísticos; Modelo jerárquico; Estimador de máxima verosimilitud; H-verosimilitud; generalized linear models; hierarchical models; h-likelihood
UR - http://eudml.org/doc/40471
ER -