I recently collected some survey data where people made a series of judgments about others' actions and their willingness to make some choice about that action.
Looking at the zero-order correlations, I see that some of the judgments are significantly correlated with the choices of the participant, whereas some others are not.
I am concerned that actual relationships may be hiding between the uncorrelated judgments and choices. Let me give a generalized example.
Imagine Predictor A and B are correlated with DV X, but Predictor C is not correlated with DV X. I was thinking that there could actually be a relationship between C and X, but that C may be negatively correlated with A or B resulting in a zero-order correlation between X and C coming out as a wash (and therefore not looking significant).
I imagine I should be able to test for this using regression, but I am not quite sure on the exact procedure. Would simply putting all A, B, and C predicting X in a regression showing that C remains insignificant be sufficient so show that it is not due to this inverse correlation?
Thank you very much for your suggestions.