Estimation in generalized linear models with random effects

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ID: 297010
1991
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Abstract
A conceptually very simple but general algorithm for the estimation of the fixed effects, random effects, and components of dispersion in generalized linear models with random effects is proposed. Conditions are described under which the algorithm yields approximate maximum likelihood or quasi-maximum likelihood estimates of the fixed effects and dispersion components, and approximate empirical Bayes estimates of the random effects. The algorithm is applied to two data sets to illustrate the estimation of components of dispersion and the modelling of overdispersion.
Reference Key
openalex_W1968578768 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Robert Schall
Journal jurnal biometrika dan kependudukan
Year 1991
DOI
10.1093/biomet/78.4.719
URL
https://doi.org/10.1093/biomet/78.4.719
Keywords Keywords not found

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