On likelihood inference in binary mixed model with an application to COPD data

DOI10.1016/J.CSDA.2004.02.001zbMath1430.62170OpenAlexW2068729564MaRDI QIDQ957114

Rahul Mukerjee, Brajendra Chandra Sutradhar

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/j.csda.2004.02.001

zbMATH Keywords

method of simulated momentssimulated maximum likelihood methodregression effectsconsistent as well as efficient estimatesvariance component of the random effects

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (4)

Fixed versus mixed effects based marginal models for clustered correlated binary data: an overview on advances and challenges ⋮ Cluster correlations and complexity in binary regression analysis using two-stage cluster samples ⋮ Inferences in generalized linear longitudinal mixed models ⋮ Robust quasi-likelihood inference in generalized linear mixed models with outliers

Uses Software

• Fahrmeir

Cites Work

• Unnamed Item
• Multivariate statistical modelling based on generalized linear models. With contributions by Wolfgang Hennevogl
• Marginal regression analysis of a multivariate binary response
• Estimation in generalized linear models with random effects
• Consistent Estimators in Generalized Linear Mixed Models
• Maximum Likelihood Algorithms for Generalized Linear Mixed Models
• On approximate likelihood inference in a poisson mixed model
• Approximate Inference in Generalized Linear Mixed Models
• Bias correction in generalised linear mixed models with a single component of dispersion

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