Which term describes the situation where the effect of one predictor on the outcome varies depending on the level of another predictor?

Which term describes the situation where the effect of one predictor on the outcome varies depending on the level of another predictor?

• A. Interaction effect
• B. Moderation effect
• C. Mediation effect
• D. Confounding effect

Answer: (A)

The key idea here is effect modification: the impact of one predictor on the outcome changes depending on the level of another predictor. In regression terms, this is called an interaction effect. You test it by including an interaction term (the product of the two predictors) in the model. If the interaction is significant, the slope of one predictor varies across levels of the other predictor, meaning the relationship isn’t the same everywhere. For example, imagine predicting exam scores from hours studied and motivation level. The benefit of studying more hours might be larger for students with high motivation and smaller for those with low motivation. That varying impact across motivation levels is an interaction effect. Why the others aren’t the right term in this context: mediation describes a chain where a predictor affects an outcome through a mediator variable, not a changing effect across another predictor. Confounding refers to a third variable that distorts the observed relationship. Moderation is often used synonymously with interaction in a conceptual sense, but the statistical term that matches “the effect of one predictor depends on another” is the interaction effect.

The key idea here is effect modification: the impact of one predictor on the outcome changes depending on the level of another predictor. In regression terms, this is called an interaction effect. You test it by including an interaction term (the product of the two predictors) in the model. If the interaction is significant, the slope of one predictor varies across levels of the other predictor, meaning the relationship isn’t the same everywhere.

For example, imagine predicting exam scores from hours studied and motivation level. The benefit of studying more hours might be larger for students with high motivation and smaller for those with low motivation. That varying impact across motivation levels is an interaction effect.

Why the others aren’t the right term in this context: mediation describes a chain where a predictor affects an outcome through a mediator variable, not a changing effect across another predictor. Confounding refers to a third variable that distorts the observed relationship. Moderation is often used synonymously with interaction in a conceptual sense, but the statistical term that matches “the effect of one predictor depends on another” is the interaction effect.