I'm now testing my hypotheses using a fixed effects model for panel-data (NBA). It's strongly balanced data. Because my hypotheses include two-way interaction and three-way interaction effects, I test my hypotheses using hierarchical regression model.
I include control and independent variables in model 1. let's say each indep var is A, B, & C.
I include two-way interaction variables in model 2 like AB, BC, and A*C
and finally I include three-way interaction variables in model 3, ABC.
My hypotheses are as follows:
H1 : A is negatively related to a dependent variable
H2 : The relationship in H1 is moderated by B
H3 : The moderation in H2 is moderated by C.
The result of the model is as follows:
Model 1 (only IV) : A and B is significant while C is insignificant.
Model 2 (two-way) : A and B is significant but AB is insignificant.(neither C nor BC nor CA)
Model 3 (three-way) : A and B is significant, AB is insignificant but ABC is significant. (other two-way interaction terms and C are also insignificant)
I plotted the result and a three-way graph is exactly same as I expected although I didn't conduct slope analysis.
In this case, can I say there is a three-way interaction effect among A,B,C?
I wonder because there is a significant three-interaction term in model 3, but two-way interaction terms are all insignificant in model 2.
I find many postings regarding interaction terms but couldn't find postings regarding both hierarchical regression model and interactions terms.