Including an interaction term between two independent variables, X₁ and X₂, allows for the following except: A)the interaction term lets the effect on Y of a change in X₁ depend on the value of X₂. B)the interaction term coefficient is the effect of a unit increase in X₁ and X₂ above and beyond the sum of the individual effects of a unit increase in the two variables alone. C)the interaction term coefficient is the effect of a unit increase in $\sqrt { \left( X _ { 1 } \times X _ { 2 } \right) }$ D)the interaction term lets the effect on Y of a change in X₂ depend on the value of X₁.

Question

Quizplus · Accepted Answer

Including an interaction term between two variables allows for the effects of one variable on the outcome to depend on the level of the other variable (A and D), and for the interaction term coefficient to represent the additional effect of the combined increase in those variables beyond their individual effects (B). However, it does not directly relate to the effect of a unit increase in the square root of their product (C), which is a different mathematical operation not described by the standard interpretation of interaction terms in regression models.

Including an Interaction Term Between Two Independent Variables, X1 and X2

Including an Interaction Term Between Two Independent Variables, X₁ and X₂