Akaike's information criterion in generalized estimating equations

Biometrics

Volumn 57, Issue 1, 2001, Pages 120-125

  Pan, W ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Akaike Information Criterion; Generalized estimating equations; Generalized linear models; Model selection; Quasi likelihood

Indexed keywords

MAXIMUM LIKELIHOOD ESTIMATION;

AKAIKE'S INFORMATION CRITERIONS; GENERALIZED ESTIMATING EQUATIONS; GENERALIZED LINEAR MODEL; MAXIMUM-LIKELIHOOD ESTIMATION; MODEL SELECTION; MODEL SELECTION CRITERIA; PENALTY TERM; PERFORMANCE; QUASI-LIKELIHOOD; RESPONSE DATA;

REGRESSION ANALYSIS;

ARTICLE; BIOSTATISTICS; DATA ANALYSIS; MATHEMATICAL MODEL; MEDICAL RESEARCH; REGRESSION ANALYSIS;

EID: 0035102570     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2001.00120.x     Document Type: Article

References (19)

1. Information theory and an extension of the maximum likelihood principle
2. A representation of the joint distribution of responses to n dichotomous items
3. Goodness-of-fit tests for GEE modeling with binary data
4. A caveat concerning independence estimating equations with multiple multivariate binary data
5. Approximate likelihood ratios for general estimating functions
6. The Wisconsin Epidemiologic Study of Diabetic Retinopathy: II. Prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years
7. On information and sufficiency
8. A deviance function for the quasi-likelihood method
9. Longitudinal data analysis using generalized linear models
10. Some comments on Cp
11. Estimating logistic regression parameters for bivariate binary data
12. A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data
13. Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method
14. The analysis of discrete longitudinal data: Commentary
15. Models for longitudinal data: A generalized estimating equation approach