Selection of Working Correlation Structure and Best Model in GEE Analyses of Longitudinal Data

DOI10.1080/03610910701539617zbMath1126.62063OpenAlexW1988216092MaRDI QIDQ5436417

Guoqi Qian, James Cui

Publication date: 16 January 2008

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610910701539617

zbMATH Keywords

AIClongitudinal studyQIC

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (11)

Criterion for the Selection of a Working Correlation Structure in the Generalized Estimating Equation Approach for Longitudinal Balanced Data ⋮ A new approach to modeling positive random variables with repeated measures ⋮ Variable selection in generalized estimating equations via empirical likelihood and Gaussian pseudo-likelihood ⋮ An R package for model fitting, model selection and the simulation for longitudinal data with dropout missingness ⋮ Robust probit linear mixed models for longitudinal binary data ⋮ Unit gamma regression models for correlated bounded data ⋮ Modeling strategies in longitudinal data analysis: covariate, variance function and correlation structure selection ⋮ Working correlation structure selection in GEE analysis ⋮ Statistical modeling of the time course of tantrum anger ⋮ Correlation Structure and Model Selection for Negative Binomial Distribution in GEE ⋮ Model selection in the weighted generalized estimating equations for longitudinal data with dropout

Uses Software

• Stata

Cites Work

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• Longitudinal data analysis using generalized linear models
• Akaike's Information Criterion in Generalized Estimating Equations
• An Extended Multivariate Random-Effects Growth Curve Model
• Generalised linear model selection by the predictive least quasi-deviance criterion
• Generalized Estimating Equations
• Monte Carlo sampling methods using Markov chains and their applications
• A new look at the statistical model identification

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