The defining characteristic of repeated measures designs is the fact that independent units—usually participants—are “crossed with” at least one of the independent variables; that is, each unit provides at least one data point for each level of one or more independent variables. In other words, in repeated measures designs, at least one of the independent variables varies “within units” and is thus referred to as a within-unit variable (e.g., within-subjects variable). In the most general sense, repeated measures designs are characterized by data that are clustered by participants (or other units) and are thus nonindependent. Repeated measures designs are different from purely between-subjects designs, in which participants are said to be “nested under” one or more independent variables.
In the simplest repeated measures design, each participant ...
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