How can adding a 2nd IV make the 1st IV significant?
For two of my main variables, the bivariate correlation coefficients (with the outcome measure) are non-significant (variable $A$ is $-.15$ with the outcome, and variable $B$ is $.04$ with the outcome, $p>.01$ in both cases). However, when entered in the second step of my regression model $A$ and $B$ add to the model ($R^2$ jumps from $.28$ to $.5$), and both variables are significant predictors ($p<.01$). Squared semi-partial correlation for variable $A$ is $.21$ and for variable $B$ it's $.12$.
I'm not sure what to make of this. Is the effect I'm seeing (in the regression model) genuine? Or is rendered suspect by virtue of the fact that the zero-order correlations are so weak? Any thoughts and comments would be appreciated.