GEE with Gaussian Estimation of the Correlations When Data Are Incomplete

DOI10.1111/j.0006-341X.2000.00528.xzbMath1060.62537WikidataQ30600459 ScholiaQ30600459MaRDI QIDQ4667478

Joseph G. Ibrahim, Geert Molenberghs, Garrett M. Fitzmaurice, Stuart R. Lipsitz

Publication date: 20 April 2005

Published in: Biometrics (Search for Journal in Brave)

zbMATH Keywords

missing datamultiple imputationbinary responseweighted estimating equations

Mathematics Subject Classification ID

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

Related Items

A Stochastic Second-Order Generalized Estimating Equations Approach for Estimating Association Parameters, Bias from the use of generalized estimating equations to analyze incomplete longitudinal binary data, Modeling Covariance Parameters for Purely Autoregressive Correlated Longitudinal Data, Bias in Estimating Association Parameters for Longitudinal Binary Responses with Drop‐Outs, Using multiple imputation with GEE with non-monotone missing longitudinal binary outcomes, Quadratic Inference Functions for Varying‐Coefficient Models with Longitudinal Data, Marginal models for zero inflated clustered data

Uses Software

• SAS/STAT

Cites Work

• Unnamed Item
• Longitudinal data analysis using generalized linear models
• Correlated Binary Regression with Covariates Specific to Each Binary Observation
• Model Robust Confidence Intervals Using Maximum Likelihood Estimators
• Inference and missing data
• The Generalized Estimating Equation Approach When Data Are Not Missing Completely at Random
• Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
• A Three-Stage Estimator for Studies with Repeated and Possibly Missing Binary Outcomes
• Maximum Likelihood Estimation of Misspecified Models