I am testing a model using SEM. I have three independent measures (seemingly covarying) impacting a DV. This is the easy part- I think. Now the hard part.. I believe that the relationship is modified by two measures that are to the most part correlated.I need to test if one of the IVs has a direct path impact on the DV due to high score on both continuous moderating variables, and all other conditions of the moderators suggest a route based upon the other two IVs.
Sounds like a 3-way interaction - you can create a product variable for the 2 continuous moderators and then multiply that with the one IV. Or, create a dummy variable for when both the 2 mediators are high and then do a 2-group analysis to see how the paths vary across the 2 groups.
Thanks for your quick response. Let me clatify the situation in more detail so I'm sure that I get what you are suggesting.
It sounds like I need to do three 3-way interactions. There are actually 3 IVs – independent measures of a somewhat theoretically distinct although interrelated construct. At this point, I am not addressing the correlation between the IVs but instead exploring the independent contributions to the DV. My hypotheses argue that the two moderators (continuous measurements -also somewhat correlated) impact the path chosen from the IVs to the DV. High/High score conditions of the IVs will choose 1 path while Low/Low will choose the other two. I need to support/negate the hypotheses of different paths for the different moderator levels (HH/LL).