Experimental Research-Repeated Measure Design

Why researcher use repeated measure design
• Researchers choose to use a repeated measures design in order to (1) conduct an experiment when few participants are available, (2) conduct the experiment more efficiently, (3) increase the sensitivity of the experiment, and (4) study changes in participants’ behavior over time.
Researchers gain several advantages when they choose to use a repeated measures design. First, repeated measures designs require fewer participants than an independent groups design, so these designs are ideal for situations in which only a small number of participants is available. Researchers who do experiments with children, the elderly or special populations such as individuals with brain injuries frequently have a small
number of participants available. Researchers choose to use repeated measures designs even when sufficient numbers of participants are available for an independent groups design. Another important advantage of repeated measures designs is that they are generally more sensitive than an independent groups design. The sensitivity of an experiment refers to the ability to detect the effect of the independent variable even if the effect
is a small one. Ideally, participants in a study respond similarly to an experimental manipulation. In practice, however, we know that people don’t all respond the same way. This error variation can be due to variations in the procedure each time the experiment is conducted or to individual differences among the participants.
Researchers also choose to use a repeated measures design because some areas of psychological research require its use. When the research question involves studying changes in participants’ behavior over time, such as in a learning experiment, a repeated measures design is needed. Further, whenever the experimental procedure requires that participants compare two or more stimuli relative to one another, a repeated measures design must be used.
THE ROLE OF PRACTICE EFFECTS IN REPEATED MEASURES DESIGNS
• Repeated measures designs cannot be confounded by individual differences variables because the same individuals participate in each condition (level) of the independent variable.
• Participants’ performance in repeated measures designs may change across conditions simply because of repeated testing (not because of the independent variable); these changes are called practice effects.
• Practice effects may threaten the internal validity of a repeated measures experiment when the different conditions of the independent variable are presented in the same order to all participants.
• There are two types of repeated measures designs (complete and incomplete) that differ in the specific ways in which they control for practice effects.
The two types of repeated measures designs are the complete and the incomplete design. The specific
techniques for balancing practice effects differ for the two repeated measures designs, but the general term used to refer to these balancing techniques is counterbalancing. In the complete design, practice effects are balanced for each participant by administering the conditions to each participant several times, using different orders each time. Each participant can thus be considered a “complete” experiment. In the incomplete design, each condition is administered to each participant only once. The order of administering the conditions is varied across participants rather than for each participant, as is the case in the complete design. Practice effects in the incomplete design average out when the results are combined for all participants.