# Continuous-by-continuous interaction using simple slopes when I have nuisance variables in my model

I've created a multiple regression predicting 1 DV from 4 IVs (all mean-centered) + 1 interaction term between two of the IVs. The interaction term is significant.

I'd like to get a nifty graph comparing the effect of one of the variables included in the interaction on the DV at particular values (say, $\pm1 SD$) of the other variable (i.e., the moderator).

I understand how to do this when I only have 3 IVs (predictor, moderator, and interaction), but how can I do this when I have 2 other IVs not involved in the interaction?

Let me know if additional info or exact numbers will help.

• Perhaps I need to regress my predicting variable onto the other two IVs (nuisance variables), and then conduct the simple slopes analysis as if the new corrected predicting variable, the moderating variable, and their interaction are the only IVs? I'm reticent to do this however, because it seems like the interaction between the moderating variable and the corrected predicting variable will be conceptually different than the original interaction. – Spencer Boucher Sep 17 '12 at 17:53