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 ...

Linear mixed-effects models are frequently used to analyze repeated measures data, because they model flexibly the within-subject correlation often present in this type of data. The most popular ...

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 ...

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

The mixed effects model for binary responses due to Conaway (1990, A Random Effects Model for Binary Data) is extended to accommodate ordinal responses in general and discrete time survival data with ...