Data may exhibit dependencies for many reasons. If a patient’s medical condition is measured across several time points, it seems unlikely that these measurements are totally unrelated. Educational ...

This course will discuss the concept of random effects, why they are called random effects and how they are incorporated in the framework of mixed models. The primary focus of the course will be to ...

Normality of random effects is a routine assumption for the linear mixed model, but it may be unrealistic, obscuring important features of among-individual variation. We relax this assumption by ...

Mixed-effects location scale models represent a powerful statistical framework designed to investigate longitudinal data. By simultaneously modelling the mean trajectories (location) and residual ...

Neuropathological studies frequently determine the positions of cells on multiple brain tissue sections taken from multiple individuals. Interest arises in group comparisons of the spatial ...