Comparison of hierarchical and marginal likelihood estimators for binary outcomes

DOI10.1016/S0167-9473(03)00033-1zbMath1429.62331OpenAlexW1974017199MaRDI QIDQ956865

Youngjo Lee, Sungcheol Yun

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(03)00033-1

zbMATH Keywords

random effectsmarginal likelihoodGauss-Hermite quadraturebinary datajoint modelhierarchical likelihood

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12)

Related Items

Limited information estimation in binary factor analysis: a review and extension ⋮ Joint hierarchical generalized linear models with multivariate Gaussian random effects ⋮ REML estimation for binary data in GLMMs ⋮ Estimating random effects in a finite Markov chain with absorbing states: Application to cognitive data ⋮ Standard error estimates in hierarchical generalized linear models ⋮ Influence diagnostics in heteroscedastic and/or autoregressive nonlinear elliptical models for correlated data ⋮ Modifications of REML algorithm for HGLMs ⋮ HGLM modelling of dropout process using a frailty model ⋮ Double Hierarchical Generalized Linear Models (With Discussion)

Uses Software

• GenStat

Cites Work

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