What design attempts to eliminate confounding variables by matching individuals in the experimental group with those in the control group?

The matched pairs design is a research method that aims to reduce the impact of confounding variables by pairing participants based on specific characteristics that are relevant to the study. In this design, one individual from a pair is assigned to the experimental group while the other is placed in the control group. This approach ensures that both groups are similar in terms of the matched characteristics, which helps in isolating the effect of the independent variable on the dependent variable.

By controlling for these characteristics, researchers can make more valid conclusions about the cause-and-effect relationship under investigation, as any differences in outcomes between the two groups can be more confidently attributed to the treatment or intervention being tested, rather than external factors.

In contrast, other designs, such as independent groups or repeated measures, do not involve matching participants based on specific attributes, which could introduce confounding variables that may affect the results. Random sampling focuses on ensuring a representative sample from the population but does not involve the specific pairing of individuals within the experimental and control groups. Therefore, the matched pairs design stands out as the method specifically aimed at eliminating confounding variables through participant matching.