Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs

Chapter 70

Repeated Measurements

Geert Verbeke and Emmanuel Lesaffre

70.1 Introduction and Case Study

In medical science, studies are often designed to investigate changes in a specific parameter that are measured repeatedly over time in the participating subjects. Such studies are called longitudinal studies, in contrast to cross-sectional studies where the response of interest is measured only once for each individual. As pointed out by Diggle et al. [1], the main advantage of longitudinal studies is that they can distinguish changes over time within individuals (longitudinal effects) from differences among people in their baseline values (cross-sectional effects).

In randomized clinical trials, where the aim is usually to compare the effect of two (or more) treatments at a specific time-point, the need and the advantage of taking repeated measures is at first sight less obvious. Indeed, a simple comparison of the treatment groups at the end of the follow-up period is often sufficient to establish the treatment effect(s) (if any) by virtue of the randomization. However, in some instances, it is important to know how the patients have reached their endpoint; i.e., it is important to compare the average profiles (over time) between the treatment groups. Furthermore, longitudinal studies can be more powerful than studies evaluating the treatments at one single time-point. Finally, follow-up studies often suffer from dropout; i.e., some patients leave the study prematurely, for known ...