Generalized Linear Mixed Models

M. Ataharul Islam () and Soma Chowdhury Biswas ()
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M. Ataharul Islam: University of Dhaka, ISRT
Soma Chowdhury Biswas: University of Chittagong, Department of Statistics

Chapter Chapter 7 in Generalized Linear Models and Extensions, 2025, pp 121-137 from Springer

Abstract: Abstract The generalized linear mixed model has emerged as a routinely employed class of linear models where both fixed and random componentsRandom component are considered for analyzing follow-up data. In a mixed model, the underlying conditional distributions for given random effects need not be Gaussian. The quasi-likelihood-based linearization, penalized quasi-likelihoodQuasi likelihood, and pseudo-likelihood-based approach are included in this chapter. This chapter provides generalized linear mixed models in a coherent manner with theoretical perspectives addressed with limitations and advantages for modeling binary, count and time-to-eventTime to event data.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-4726-2_7

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DOI: 10.1007/978-981-96-4726-2_7

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