Correlated data frequently arise from cross-sectional studies with complex cluster design
because individuals from the same cluster or region share some common characteristics …

Multivariate data are commonly analyzed using one of two approaches: a conditional
approach based on generalized linear latent variable models (GLLVMs) or some variation …

This article briefly explains the simultaneous spatial durbin panel (SSDP) model. The study
of the SSDP model is substantial because it can explain the interaction between geographic …

To obtain regression parameter estimates in generalized estimation equation modeling,
whether in longitudinal or spatially correlated data, it is necessary to specify the structure of …

Generalized estimating equations (GEE) is one of the most commonly used methods for
regression analysis of longitudinal data, especially with discrete outcomes. The GEE method …

Objectives The FDA recommends the use of anchor-based methods and empirical
cumulative distribution function (eCDF) curves to establish a meaningful within-patient …

Generalized estimating equations (GEE) incorporate a working correlation structure that is
important because the more accurately this structure reflects the true structure, the more …

The generalized estimating equations (GEE) procedure is a common approach for
regression analyses of correlated responses, which is common for data obtained in …

However, because Y a () does not appear on the causal diagram, this step does not seem to
be justified from the causal graph alone and requires knowledge that is not reflected by the …

Background: In repeated measures data the observations tend to be correlated within each
subject and such data are often analysed using Generalized Estimating Equations which is …