MODERATOR EFFECTS

What if an independent–dependent variable relationship is affected by another independent variable? 

• This situation is termed a moderator effect, which occurs when the moderator variable, a second independent variable, changes the form of the relationship between another independent variable and the dependent variable. 
• It is also known as an interaction effect and is similar to the interaction term found in analysis of variance and multivariate analysis of variance.

(Nguồn: https://uedufy.com/how-to-perform-moderation-analysis-in-spss/)

Adding the Moderator Effect

• The moderator term is a compound variable formed by multiplying X1 by the moderator X2, 

(Nguồn: Hair et al, 2013)

• Because of the multicollinearity among the old and new variables, an approach similar to testing for the significance of polynomial (nonlinear) effects is employed. 
• To determine whether the moderator effect is significant, the researcher follows a three-step process:
1. Estimate the original (unmoderated) equation.
2. Estimate the moderated relationship (original equation plus moderator variable)
3. Assess the change in R2: If it is statistically significant, then a significant moderator effect is present. Only the incremental effect is assessed, not the significance of individual variables.

Interpreting Moderator Effects.

• The b3 coefficient, the moderator effect, indicates the unit change in the effect of X1 as X2 changes. The b1 and b2 coefficients now represent the effects of X1 and X2, respectively, when the other independent variable is zero.
• In the unmoderated relationship, the b1 coefficient represents the effect of X1 across all levels of X2, and similarly for b2. 
• To determine the total effect of an independent variable, the separate and moderated effects must be combined.

(Nguồn: https://link.springer.com/article/10.1007/s40815-020-00848-3)

(Những nội dung này trích từ sách của Hair et al. (2013))

Nguồn:

• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (8th ed.). Boston: Cengage.