What type of research design would you use to control for individual differences in participants?

The matched participants design is a research approach that is specifically designed to control for individual differences among participants. In this method, pairs of participants are matched based on specific characteristics that could influence the outcome of the study, such as age, gender, IQ, or other relevant traits. Each member of the pair is then assigned to different experimental conditions. This matching helps ensure that any differences observed in the dependent variable can be more confidently attributed to the independent variable rather than individual differences among participants.

Using this design minimizes variability due to participant characteristics, helping improve the validity of the findings. Researchers can make more accurate comparisons between groups since each participant in one group is paired with someone similar in the other group, which is not a feature of the other designs.

In contrast, independent group designs involve randomly assigning participants to different conditions without controlling for specific traits, potentially leading to greater individual differences between groups. Repeated measures designs, while reducing the impact of individual differences over time, can introduce issues related to practice effects or fatigue since the same participants are used in all conditions. Random allocation aids in distributing individuals randomly to groups but does not account for matching on key characteristics. Thus, the matched participants design is the most effective for controlling for individual differences among participants.