REML estimation for binary data in GLMMs

DOI10.1016/j.jmva.2006.11.009zbMath1113.62087OpenAlexW1982003846MaRDI QIDQ2372134

Maengseok Noh, Youngjo Lee

Publication date: 11 July 2007

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2006.11.009

zbMATH Keywords

Laplace methodrestricted likelihoodgeneralized linear mixed modelsrestricted maximum likelihoodhierarchical likelihoodhierarchical generalized linear models

Mathematics Subject Classification ID

Related Items (27)

Joint hierarchical generalized linear models with multivariate Gaussian random effects ⋮ Inference on finite population categorical response: nonparametric regression-based predictive approach ⋮ Dealing with separation or near-to-separation in the model for multinomial response with application to childhood health seeking behavior data from a complex survey ⋮ Unnamed Item ⋮ Fast estimation of multiple group generalized linear latent variable models for categorical observed variables ⋮ Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations ⋮ Multilevel cumulative logistic regression model with random effects: application to British Social Attitudes Panel Survey data ⋮ Frailty modelling approaches for semi-competing risks data ⋮ Maximum likelihood estimation based on the Laplace approximation for p₂ network regression models ⋮ Standard error estimates in hierarchical generalized linear models ⋮ Hierarchical likelihood approach to non-Gaussian factor analysis ⋮ Conditional Akaike information criterion for generalized linear mixed models ⋮ Hierarchical likelihood methods for nonlinear and generalized linear mixed models with missing data and measurement errors in covariates ⋮ Likelihood inference for models with unobservables: another view ⋮ A penalized h-likelihood variable selection algorithm for generalized linear regression models with random effects ⋮ Alternating imputation posterior estimation of models with crossed random effects ⋮ Additive multilevel item structure models with random residuals: item modeling for explanation and item generation ⋮ Approximate conditional inference in mixed-effects models with binary data ⋮ Estimation in the probit normal model for binary outcomes using the SAEM algorithm ⋮ Modifications of REML algorithm for HGLMs ⋮ Estimation and prediction for spatial generalized linear mixed models using high order Laplace approximation ⋮ Prediction interval for disease mapping using hierarchical likelihood ⋮ Multiple imputation for multilevel data with continuous and binary variables ⋮ Hierarchical-likelihood approach for nonlinear mixed-effects models ⋮ Accuracy of Laplace approximation for discrete response mixed models ⋮ Directional wavelets and a wavelet variogram for two-dimensional data ⋮ Generalized Additive Models for Location, Scale and Shape

Uses Software

• GenStat

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions
• Comparison of hierarchical and marginal likelihood estimators for binary outcomes
• Comparison of hierarchical likelihood versus orthodox best linear unbiased predictor approaches for frailty models
• On the Strong Law of Large Numbers and Related Results for Quasi-Stationary Sequences
• Estimation in generalized linear models with random effects
• Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
• REML Estimation with Exact Covariance in the Logistic Mixed Model
• Maximum Likelihood Variance Components Estimation for Binary Data
• Bias Correction in Generalized Linear Mixed Models With Multiple Components of Dispersion
• Maximum Likelihood Algorithms for Generalized Linear Mixed Models
• Another Look at the Salamander Mating Data: A Modified Laplace Approximation Approach
• The Effect of Improper Priors on Gibbs Sampling in Hierarchical Linear Mixed Models
• Empirical Bayes Estimation of Random Effects Parameters in Mixed Effects Logistic Regression Models
• Approximate Inference in Generalized Linear Mixed Models
• Bias correction in generalised linear mixed models with a single component of dispersion
• Applied Bayesian Modeling and Causal Inference from Incomplete‐Data Perspectives
• Recovery of inter-block information when block sizes are unequal

This page was built for publication: REML estimation for binary data in GLMMs