ABSTRACT
This book presents the Bayesian approach to the analysis of repeated measures. As such, the book is unique in that it is the only one from a Bayesian viewpoint to present the basic ideas about analyzing repeated measures and associated designs. In repeated measures, measurements of the same experimental unit are taken over time or over different study conditions. In a repeated measure study, the main aim is to determine the average value or mean profile of the individual over the range the measurements are observed. Thus, the focus is on the within-individual change of the average response. Repeated measure studies differ from cross-sectional designs, if the same individual is followed over time; on the other hand, with the cross-sectional design, different individuals appear throughout the observation period. A good example of a cross-sectional study occurs in clinical trials, where one group of subjects receives the treatment under study and another a different treatment (or placebo). Of course, it is possible that the same individual can receive the treatment at various time points, followed by receiving another treatment at later time points.
