What does an interaction effect in a two-way ANOVA describe?

What does an interaction effect in a two-way ANOVA describe?

• A. Effects on the dependent variable of two or more independent variables working together; the DV responds differently at levels of the IV
• B. Only the main effects of each IV
• C. A random error effect
• D. Correlation between the IVs

Answer: (A)

An interaction describes how the effect of one independent variable on the dependent variable changes depending on the level of the other independent variable. In other words, the two factors combine to influence the outcome in a way that isn’t just the sum of their separate effects. For example, the benefit of a treatment might be larger for one age group than another, so the treatment effect isn’t consistent across age groups. If there’s no interaction, each factor has a consistent, additive effect regardless of the other factor’s level. In ANOVA, a significant interaction term signals this non-additive, joint influence.

An interaction describes how the effect of one independent variable on the dependent variable changes depending on the level of the other independent variable. In other words, the two factors combine to influence the outcome in a way that isn’t just the sum of their separate effects. For example, the benefit of a treatment might be larger for one age group than another, so the treatment effect isn’t consistent across age groups. If there’s no interaction, each factor has a consistent, additive effect regardless of the other factor’s level. In ANOVA, a significant interaction term signals this non-additive, joint influence.