Comparison of PQL and Laplace 6 estimates of hierarchical linear models when comparing groups of small incident rates in cluster randomised trials

DOI10.1016/j.csda.2006.10.005zbMath1161.62386OpenAlexW2072832768MaRDI QIDQ1019918

Rafael E. Diaz

Publication date: 29 May 2009

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

Full work available at URL: https://doi.org/10.1016/j.csda.2006.10.005

zbMATH Keywords

cluster randomisationLaplace 6penalized quasilikelihood (PQL)

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Monte Carlo methods (65C05)

Related Items (4)

Penalized likelihood approach for simultaneous analysis of survival time and binary longitudinal outcome ⋮ Alternating imputation posterior estimation of models with crossed random effects ⋮ Comparisons of computational methods for clustered binary data ⋮ Logistic Regression With Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

Cites Work

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• Longitudinal data analysis using generalized linear models
• Variance component testing in generalised linear models with random effects
• Bias Correction in Generalized Linear Mixed Models With Multiple Components of Dispersion
• Interpreting Parameters in the Logistic Regression Model with Random Effects
• Approximate Inference in Generalized Linear Mixed Models
• Improved Approximations for Multilevel Models with Binary Responses
• Bias correction in generalised linear mixed models with a single component of dispersion

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