A repeated-measures design is one in which multiple, or repeated; measurements are made on each experimental unit. The experimental unit could be a person or an animal, and repeated measurements might be taken serially in time, such as in weekly systolic blood pressures or monthly weights. The repeated assessments might be measured under different experimental conditions.
Repeated measurements on the same experimental unit can also be taken at a point in time. For example, it might be of interest to measure the diameter of each of several lesions within each person or animal in a study. The dependency, or correlation, among responses measured in the same individual is the defining feature of a repeated-measures design. This correlation necessitates a statistical analysis that appropriately accounts for the dependency among measurements within the same experimental unit, which results in a more precise and powerful statistical analysis.
Repeated-measures analysis encompasses a spectrum of applications, which in the simplest case is a generalization of the paired t test.1 a repeated-measures within-subjects design can be thought of as an extension of the paired t test that involves ≥3 assessments in the same experimental unit. Repeated-measures analysis can also handle more complex, higher-order designs with within-subject components and multifactor between-subjects components. The focus here is on within-subjects designs.