What is needed to make a repeated measures design a true experimental design?

What is needed to make a repeated measures design a true experimental design?

• A. Randomizing the order of treatments
• B. Lack of randomization acceptable
• C. Using only one level of the independent variable
• D. Using different participants for each condition

Answer: (A)

In repeated measures designs, the same participants experience all levels of the independent variable, which helps control for individual differences but makes results vulnerable to order effects like practice, fatigue, or carryover. Randomizing the order in which treatments are presented distributes those potential sequence effects across conditions, so they don’t systematically bias any single treatment. This randomization strengthens internal validity and supports causal conclusions about the effect of the manipulated variable, effectively making the design a true experimental one. The other options don’t fit because lacking randomization leaves order effects unchecked; using only one level of the independent variable doesn’t test any effect of interest; and using different participants for each condition changes the design to between-subjects, not repeated measures, and reintroduces between-person variability that the repeated measures approach is meant to control.

In repeated measures designs, the same participants experience all levels of the independent variable, which helps control for individual differences but makes results vulnerable to order effects like practice, fatigue, or carryover. Randomizing the order in which treatments are presented distributes those potential sequence effects across conditions, so they don’t systematically bias any single treatment. This randomization strengthens internal validity and supports causal conclusions about the effect of the manipulated variable, effectively making the design a true experimental one.

The other options don’t fit because lacking randomization leaves order effects unchecked; using only one level of the independent variable doesn’t test any effect of interest; and using different participants for each condition changes the design to between-subjects, not repeated measures, and reintroduces between-person variability that the repeated measures approach is meant to control.