On Adaptive Gauss-Hermite Quadrature for Estimation in GLMM’s

DOI10.1007/978-981-15-1960-4_9zbMath1445.62167OpenAlexW2997729263MaRDI QIDQ3305494

Nishika Ranathunga, Paul V. Kabaila

Publication date: 7 August 2020

Published in: Communications in Computer and Information Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-981-15-1960-4_9

zbMATH Keywords

maximum likelihood estimationimportance samplingadaptive Gauss-Hermite quadraturegeneralized linear mixed models (GLMM)

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Generalized linear models (logistic models) (62J12) Numerical quadrature and cubature formulas (65D32)

Related Items (1)

CONFIDENCE INTERVALS IN GENERAL REGRESSION MODELS THAT UTILISE UNCERTAIN PRIOR INFORMATION

Uses Software

• Stata
• GLLAMM

Cites Work

• On the Effect of the Number of Quadrature Points in a Logistic Random Effects Model: An Example
• Mixed Models
• Logistic Regression With Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages
• Longitudinal Data Analysis
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: On Adaptive Gauss-Hermite Quadrature for Estimation in GLMM’s