I am considering a study I'll note below, but have limited statistical experience. Accordingly I am seeking insights on which tests are appropriate given the data and what I am looking to test.

In this potential study I would examine three variables, let us call them variable A, variable B, and variable C. All are interval variables. My prediction is that higher scores of variable B are related to higher scores of variable C (previous regression analyses have shown this to be true). Further, I predict that the magnitude of variable A will impact the effect of variable B on variable C. That is, I predict that subjects with low scores on variable A will see a greater impact from variable B on variable C than subjects who have high scores on variable A.

The literature has indicated that there are other factors besides variable B which impact variable C. Accordingly I'm looking to incorporate these other factors into the analysis in order to better isolate the impact of variable B on variable C.

Thus far I've been advised to utilize the hierarchical regression method as an exploratory analysis to see if adding a third variable will change the predictive power of the model. In phase two I would then incorporate the variables deemed significant in the final model. I am unclear on how to account for the other factors the literature has noted that may impact variable C in this analysis, however.

If you have any insights on the information above or have suggested readings to help myself better understand how to approach this type of problem, I would greatly appreciate your input.

Thanks!