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Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles: a simulation study

Author
Casals, M.; Langohr, K.; Carrasco, J.L.; Rönnegård, L.
Type of activity
Journal article
Journal
SORT: statistics and operations research transactions
Date of publication
2015-12
Volume
39
Number
2
First page
281
Last page
308
Repository
http://hdl.handle.net/2117/84717 Open in new window
URL
http://www.idescat.cat/sort/ Open in new window
Abstract
Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three differen...
Citation
Casals, M., Langohr, K., Carrasco, J., Rönnegård, L. Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles: a simulation study. "SORT: statistics and operations research transactions", Desembre 2015, vol. 39, núm. 2, p. 281-308.
Keywords
Estimation methods, Poisson generalized linear mixed models, overdispersion, simu- lation study, sport injuries, statistical principles
Group of research
GRBIO - Biostatistics and Bioinformatics Research Group

Participants

  • Casals Toquero, Martí  (author)
  • Langohr, Klaus  (author)
  • Carrasco Jordán, Josep Lluís  (author)
  • Rönnegård, Lars  (author)

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