# $R^2$ value and associated significance for each predictor in regression

I would like to measure the $R^2$ value for each of the predictors in my regression analysis. I understand that I can either use the $R^2$ change in a hierarchical regression, or I can square the coefficients in a partial correlation. I'm favouring the latter, because as I understand it the order of the predictors in the hierarchical regression can affect the changes in $R^2$ value, with higher values given to variables entered earlier on.

One of my predictor variables is dichotomous, can I use this in a partial correlation?

If so, how do I go about assessing the significance associated with each predictor as I would by looking at the F-change in a hierarchical regression?