Generalized estimating equations: Notes on the choice of the working correlation matrix

Methods of Information in Medicine

Volumn 49, Issue 5, 2010, Pages 419-420

  Molenberghs, G ^a  

^a HASSELT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

METHODOLOGY; NOTE; STATISTICAL MODEL; STATISTICS;

MODELS, STATISTICAL; STATISTICS AS TOPIC;

EID: 79952279317     PISSN: 00261270     EISSN: None     Source Type: Journal    
DOI: 10.1055/s-0038-1625134     Document Type: Editorial

References (9)

1. Ziegler A, Vens M. Generalized Estimating Equa-tions: Notes on the Choice of the Working Correlation Matrix. Methods Inf Med 2010; 49 (5): 421-425
2. Breitung J, Chaganty NR, Daniel RM, Kenward MG, Lechner M, Martus P, Sabo RT, Wang Y-G, Zorn C. Discussion of "Generalized Estimating Equations: Notes on the Choice of the Working Correlation Matrix". Methods Inf Med 2010; 49 (5): 426-432
3. Zeger SL, Liang K-Y, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics 1988; 44, 1049-1060
4. Molenberghs G, Kenward MG. Semi-parametric marginal models for hierarchical data and their corresponding full models. Computational Statistics and Data Analysis 2009; 54, 585-597
5. Molenberghs G, Verbeke G. Models for Discrete Longitudinal Data. New York: Springer; 2005.
6. Molenberghs G, Kenward MG, Verbeke G, Teshome Ayele B. Pseudo-likelihood estimation for incomplete data. Statistica Sinica (in press).
7. Beunckens C, Sotto C, Molenberghs G. A simulation study comparing weighted estimating equations with multiple imputation based estimating equations for longitudinal binary data. Computational Statistics and Data Analysis 2008; 52, 1533-1548
8. Molenberghs G, Kenward MG. Missing Data in Clinical Studies. Chichester: John Wiley & Sons; 2007.
9. Fitzmaurice GM, Molenberghs G, Lipsitz SR. Regression models for longitudinal binary responses with informative dropouts. Journal of the Royal Statistical Society, Series B, 1995; 57: 691-704.