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.
