Which statement describes an independent factorial design?

Which statement describes an independent factorial design?

• A. An experimental design with two or more predictors that is tested within the same participants
• B. An experimental design with two or more predictors, all manipulated using different participants, forming a factorial structure
• C. A design with one predictor tested across time
• D. A randomized block design

Answer: (B)

Independent factorial designs involve manipulating two or more factors, with each participant assigned to only one combination of factor levels so that observations are independent. This setup creates a factorial structure where all levels of the factors are crossed. The statement describes two or more predictors that are each manipulated using different participants, forming the full crossed set of conditions. That means you’d have every combination of the factor levels represented, and different participants in each combination, which is the essence of a between-subjects factorial design. For example, a 2x2 between-subjects design might combine drug vs. placebo with low vs. high cognitive load, with participants assigned to one of the four cells and no one experiencing multiple conditions. This is different from within-subjects (where the same participants experience multiple levels of a factor), a longitudinal time-based design (predictor tested across time), or a blocking design (which uses blocks to control variance rather than crossing factors).

Independent factorial designs involve manipulating two or more factors, with each participant assigned to only one combination of factor levels so that observations are independent. This setup creates a factorial structure where all levels of the factors are crossed.

The statement describes two or more predictors that are each manipulated using different participants, forming the full crossed set of conditions. That means you’d have every combination of the factor levels represented, and different participants in each combination, which is the essence of a between-subjects factorial design. For example, a 2x2 between-subjects design might combine drug vs. placebo with low vs. high cognitive load, with participants assigned to one of the four cells and no one experiencing multiple conditions.

This is different from within-subjects (where the same participants experience multiple levels of a factor), a longitudinal time-based design (predictor tested across time), or a blocking design (which uses blocks to control variance rather than crossing factors).