Which term describes a design that systematically manipulates more than one independent variable to study potential interaction effects?

Which term describes a design that systematically manipulates more than one independent variable to study potential interaction effects?

• A. Multi-factorial design
• B. Factorial design
• C. Related design
• D. Between-subjects design

Answer: (A)

When you want to uncover whether the effect of one variable changes across levels of another, you design that manipulates two or more independent variables together. This is called a factorial design, also known as a multifactorial design. By setting up all combinations of the factor levels (a full factorial design), you can estimate not only the main effects of each factor but also the interaction between factors—whether the effect of one factor depends on the level of the other. For example, if you vary dose level (low vs high) and type of feedback (positive vs negative), a factorial design lets you see if the impact of dose on the outcome changes with the type of feedback. The analysis typically uses ANOVA to test both main effects and the interaction term. It can be between-subjects, within-subjects, or mixed, depending on how participants are assigned to conditions. The standard term to describe this approach is factorial design; multifactorial is a synonymous way of describing multiple manipulated factors.

When you want to uncover whether the effect of one variable changes across levels of another, you design that manipulates two or more independent variables together. This is called a factorial design, also known as a multifactorial design. By setting up all combinations of the factor levels (a full factorial design), you can estimate not only the main effects of each factor but also the interaction between factors—whether the effect of one factor depends on the level of the other. For example, if you vary dose level (low vs high) and type of feedback (positive vs negative), a factorial design lets you see if the impact of dose on the outcome changes with the type of feedback. The analysis typically uses ANOVA to test both main effects and the interaction term. It can be between-subjects, within-subjects, or mixed, depending on how participants are assigned to conditions. The standard term to describe this approach is factorial design; multifactorial is a synonymous way of describing multiple manipulated factors.