GEECAT and GEEGOR: computer programs for the analysis of correlated categorical response data.
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Summary
GEECAT and GEEGOR are two user-friendly SAS macros for the analysis of clustered, correlated categorical response data which extend the generalized estimating equation (GEE) approach of Liang and Zeger.
- Type
- article
- Published
- 1999-01-01
- Cited by
- 29
- References
- 11
- OpenAlex
- https://openalex.org/W2046051215
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:33461397
Keywords
Categorical variable, Gee, Generalized estimating equation, Marginal model, Macro
References
- Regression Models for Ordinal Data
- Analyzing bivariate ordinal data using a global odds ratio
- Longitudinal data analysis for discrete and continuous outcomes.
- Correlated binary regression with covariates specific to each binary observation.
- Analysis of repeated categorical data using generalized estimating equations.
- A Class of Bivariate Distributions
- The Wisconsin epidemiologic study of diabetic retinopathy. II. Prevalence and risk of diabetic retinopathy when age at diagnosis is less than 30 years.
- Global cross-ratio models for bivariate, discrete, ordered responses.
- Auranofin therapy and quality of life in patients with rheumatoid arthritis. Results of a multicenter trial.
- Longitudinal data analysis using generalized linear models
- Multivariate Regression Analyses for Categorical Data
- A Class of Bivariate Distributions
- Analyzing Bivariate Ordinal Data Using a Global Odds Ratio
Cited by
- R Package multgee: A Generalized Estimating Equations Solver for Multinomial Responses
- Simulation-Based Study Comparing Multiple Imputation Methods for Non-Monotone Missing Ordinal Data in Longitudinal Settings
- GEE for longitudinal ordinal data: Comparing R-geepack, R-multgee, R-repolr, SAS-GENMOD, SPSS-GENLIN
- A Simulation Study Comparing Multiple Imputation Methods for Incomplete Longitudinal Ordinal Data
- Association of polymorphisms in the apolipoprotein E region with susceptibility to and progression of multiple sclerosis.
- Dietary patterns and breast density in the Minnesota Breast Cancer Family Study
- Generalized Estimating Equation Models for Correlated Data: A Review with Applications
- Regression models for unbalanced longitudinal ordinal data: computer software and a simulation study
- Urinary Tract Infections in Postmenopausal Women: Effect of Hormone Therapy and Risk Factors
- A Bayesian analysis of bivariate ordinal data: Wisconsin epidemiologic study of diabetic retinopathy revisited
- Bivariate versus univariate ordinal categorical data with reference to an ophthalmologic study
- Applications of the estimating equations theory to genetic epidemiology: a review
- Incidence of sleep-disordered breathing in an urban adult population: the relative importance of risk factors in the development of sleep-disordered breathing.
- Mediterranean Diet and Breast Density in the Minnesota Breast Cancer Family Study
- Experimental Comparison of Hygroscopic Expansion in Three Different Composite Resins
- Warfarin Therapy in the HIV Medical Home Model: Low Rates of Therapeutic Anticoagulation Despite Adherence and Differences in Dosing Based on Specific Antiretrovirals
- A Bayesian analysis of the 4‐year follow‐up data of the Wisconsin epidemiologic study of diabetic retinopathy
- A note on the estimation of the multinomial logistic model with correlated responses in SAS
- Families Matter in Long-Term Care: Results of a Group-Randomized Trial
- Modeling Paired Ordinal Response Data
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