Test Bank of Research Methods in Psychology 10th Edition by Shaughnessy
Repeated Measures Designs
Short Answer Questions
1. (p. 220-221) Cite two reasons why a researcher might choose to use a repeated measures design.
The four reasons cited in the text are that repeated measures designs are ideal when only a small number of subjects is available; that repeated measures designs are more convenient and efficient; that repeated measures designs are generally more sensitive; and that repeated measures designs can be used to study changes in participants’ behavior over time or across stimuli.
2. (p. 224) Provide brief answers to the following question regarding the repeated measures designs.
What distinguishes the complete repeated measures design from the incomplete repeated measures design?
In the complete repeated measures design each subject experiences each condition at least twice such that the results are interpretable for each subject (i.e., practice effects are balanced within subjects). In the incomplete repeated measures design each subject experiences each condition exactly once so the results are interpretable only by averaging across subjects (i.e., conditions of the independent variable are confounded with practice effects within subjects).
3. (p. 224-227, 230-232) Provide brief answers to the following question regarding the repeated measures designs.
What techniques are used in the complete and incomplete repeated measures designs to balance practice effects?
Block randomization and ABBA counterbalancing are used to balance practice effects in the complete repeated measures design, and some researchers use simple randomization in which new random orders are created for each subject. All possible orders or selected specific orders (Latin Square and random starting order with rotation) are used to balance practice effects in the incomplete repeated measures design.
4. (p. 227-228) Explain why ABBA counterbalancing would be ineffective in balancing practice effects in the complete repeated measures design when the practice effects involve an abrupt initial change followed by little change thereafter.
ABBA counterbalancing is most effective when practice effects are linear, meaning that each trial adds the same amount of practice and each condition accumulates the same amount of practice across the trials. When practice effects are nonlinear (as in this case), practice effects will contribute less to performance in the conditions administered following the initial trial. Practice effects will not be balanced across the conditions.
5. (p. 230-231) What are one advantage and one disadvantage of using all possible orders to balance practice effects in the incomplete repeated measures design?
The advantage of using all possible orders, the preferred method for balancing practice effects in the incomplete repeated measures design, is that every condition occurs in every ordinal position and precedes and follows every condition in every ordinal position. The disadvantage of using all possible orders is that it is generally limited to experiments with four or fewer conditions. [With four conditions, there are 24 possible orders, requiring at least one subject assigned to each.]
6. (p. 237-238) Define differential transfer and describe one method a researcher could use to detect whether differential transfer is a problem in a repeated measures experiment.
Differential transfer occurs when performance in one condition differs depending on the condition that precedes it. That is, the effects of one condition persist and influence performance differently in subsequent conditions. The best way to determine whether differential transfer is a problem is to test the independent variable in two separate experiments, a repeated measures experiment and a random groups experiment. If the results of the two experiments differ, differential transfer may be a problem. A second method is to examine the results for the first ordinal position in an incomplete design, which represents an random groups design (if participants are randomly assigned to different orders). If the results differ when compared to the repeated measures design as a whole, then differential transfer may be a problem.
7. (p. 220, 222-224) Identify the differences between the random groups design and the repeated measures design in terms of how the independent variable is manipulated and what potential confounding variable must be balanced in each design. What method(s) are available for balancing in each design?
In a random groups design the researcher manipulates the independent variable such that different groups of participants experience each level of the independent variable. Individual differences among participants across the conditions of the experiment must be balanced; random assignment to conditions is the preferred method for balancing individual differences variables. In the repeated measures design the independent variable is manipulated such that the same group of participants experiences every condition of the experiment. Practice effects due to repeated measurement must be counterbalanced in repeated measures designs. In the complete repeated measures design, in which each participants experiences every condition more than once, ABBA counterbalancing or block randomization may be used to balance practice effects across conditions. In the incomplete design, in which each participant experiences every condition exactly once, all possible orders or selected orders may be used to balance practice effects.