Fitting marginal models in small samples: a simulation study of marginalized multilevel models and generalized estimating equations

Cites Work

Longitudinal data analysis using generalized linear models
A note on marginalization of regression parameters from mixed models of binary outcomes
A Covariance Estimator for GEE with Improved Small‐Sample Properties
Small-Sample Adjustments for Wald-Type Tests Using Sandwich Estimators
Conditional and marginal models: another view (with comments and rejoinder)
Misspecified maximum likelihood estimates and generalised linear mixed models
Clustered data with small sample sizes: Comparing the performance of model-based and design-based approaches
Small-sample adjustments to tests with unbalanced repeated measures assuming several covariance structures
Models for Longitudinal Data: A Generalized Estimating Equation Approach
Correlated Binary Regression with Covariates Specific to Each Binary Observation
Small Sample Inference for Fixed Effects from Restricted Maximum Likelihood
A Note on the Efficiency of Sandwich Covariance Matrix Estimation
Marginally Specified Logistic‐Normal Models for Longitudinal Binary Data
Interpreting Parameters in the Logistic Regression Model with Random Effects
Small Sample Correction for the Variance of GEE Estimators
Small Sample Inference for Clustered Data
Marginalized Models for Moderate to Long Series of Longitudinal Binary Response Data
Practical marginalized multilevel models

This page was built for publication: Fitting marginal models in small samples: a simulation study of marginalized multilevel models and generalized estimating equations