Generalized Estimating Equations

Hardin, James W., Hilbe, Joseph

ISBN 10: 1584883073 / ISBN 13: 9781584883074

Editore: CRC Press LLC, 2002

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Codice articolo 51716133-6

Dati bibliografici

• Titolo: Generalized Estimating Equations
• Editore: CRC Press LLC
• Data di pubblicazione: 2002
• Lingua: Inglese
• ISBN 10: 1584883073
• ISBN 13: 9781584883074
• Rilegatura: Rilegato
• Condizione: Very Good

Descrizione articolo

Riassunto

Although powerful and flexible, the method of generalized linear models (GLM) is limited in its ability to accurately deal with longitudinal and clustered data. Developed specifically to accommodate these data types, the method of Generalized Estimating Equations (GEE) extends the GLM algorithm to accommodate the correlated data encountered in health research, social science, biology, and other related fields. Generalized Estimating Equations provides the first complete treatment of GEE methodology in all of its variations. After introducing the subject and reviewing GLM, the authors examine the different varieties of generalized estimating equations and compare them with other methods, such as fixed and random effects models. The treatment then moves to residual analysis and goodness of fit, demonstrating many of the graphical and statistical techniques applicable to GEE analysis. With its careful balance of origins, applications, relationships, and interpretation, this book offers a unique opportunity to gain a full understanding of GEE methods, from their foundations to their implementation. While equally valuable to theorists, it includes the mathematical and algorithmic detail researchers need to put GEE into practice.

Contenuti

INTRODUCTION
Notational Conventions
A Short Review of Generalized Linear Models
Software
Exercises
MODEL CONSTRUCTION AND ESTIMATING EQUATIONS
Independent Data
Estimating the Variance of the Estimates
Panel Data
Estimation
Summary
Exercises
GENERALIZED ESTIMATING EQUATIONS
Population-Averaged (PA) and Subject-Specific (SS) Models
The PA-GEE for GLMs
The SS-GEE for GLMs
The GEE2 for GLMs
GEEs for Extensions of GLMs
Further Developments and Applications
Missing Data
Choosing an Appropriate Model
Summary
Exercises
RESIDUALS, DIAGNOSTICS, AND TESTING
Criterion Measures
Analysis of Residuals
Deletion Diagnostics
Goodness of Fit (Population-Averaged Models)
Testing Coefficients in the PA-GEE Model
Assessing the MCAR Assumption of PA-GEE Models
Summary
Exercises
PROGRAMS AND DATASETS
Programs
Datasets
References
Author Index
Subject Index