Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Marek Molas, Emmanuel Lesaffre
Title: Hierarchical Generalized Linear Models: The R Package HGLMMM
Abstract: The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution. The distribution of random effects can be specified as Gaussian, gamma, inverse-gamma or beta. Complex structures as multi-membership design or multilevel designs can be handled. Further, dispersion parameters of random components and the residual dispersion (overdispersion) can be modeled as a function of covariates. Overdispersion parameter can be fixed or estimated. Fixed effects in the mean structure can be estimated using extended likelihood or a first order Laplace approximation to the marginal likelihood. Dispersion parameters are estimated using first order adjusted profile likelihood.

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Paper: Hierarchical Generalized Linear Models: The R Package HGLMMM     Download PDF (Downloads: 30083)
HGLMMM_0.1.2.tar.gz: R source package Download (Downloads: 735; 45KB)
v39i13.R: R example code from the paper Download (Downloads: 870; 11KB)

DOI: 10.18637/jss.v039.i13

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.