Generalized Linear Mixed Models - Overview

Abstract

In applied sciences, one is often confronted with the collection of correlated data or otherwise hierarchical data. This generic term embraces a multitude of data structures, such as multivariate observations, clustered data, repeated measurements, longitudinal data, and spatially correlated data. In particular, studies are often designed to investigate changes in a specific outcome which is measured repeatedly over time in the participating persons. This is in contrast to cross-sectional studies where the response of interest is measured only once for each individual. Longitudinal studies are conceived for the investigation of such changes, together with the evolution of relevant covariates.