Hierarchical Generalized Linear Models: The R Package HGLMMM

Marek Molas and Emmanuel Lesaffre

Journal of Statistical Software, 2011, vol. 039, issue i13

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.

Date: 2011-03-09
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:039:i13

DOI: 10.18637/jss.v039.i13

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