Generalized Estimating Equation (GEE) is a marginal model popularly applied for
longitudinal/clustered data analysis in clinical trials or biomedical studies. We provide a …

Robust statistics is an extension of classical statistics that specifically takes into account the
concept that the underlying models used to describe data are only approximate. Its basic …

We consider the penalized generalized estimating equations (GEEs) for analyzing
longitudinal data with high-dimensional covariates, which often arise in microarray …

Selecting an appropriate working correlation structure is pertinent to clustered data analysis
using generalized estimating equations (GEE) because an inappropriate choice will lead to …

Classical statistics relies largely on parametric models. Typically, assumptions are made on
the structural and the stochastic parts of the model and optimal procedures are derived …

The Generalized Estimating Equations (GEE) method is one of the most commonly used
statistical methods for the analysis of longitudinal data in epidemiological studies. A working …

In this paper robust statistical procedures are presented for the analysis of skewed and
heavy-tailed outcomes as they typically occur in health care data. The new estimators and …

Mixed effects models have become a critical tool in all areas of psychology and allied fields.
This is due to their ability to account for multiple random factors, and their ability to handle …

Model selection for marginal regression analysis of longitudinal data is challenging owing to
the presence of correlation and the difficulty of specifying the full likelihood, particularly for …

Background Feature selection is commonly employed for identifying collectively-predictive
biomarkers and biosignatures; it facilitates the construction of small statistical models that …