An interaction effect groups the observations on the basis of the values of all the constituent classification factors and defines a different parameter in the model for each group. That is, two observations are in different groups with respect to the interaction if they have different values for any of the factors in the interaction. Interactions account for differences in how the response reacts to one factor depending on the values of other factors.