When computing the correlation between two variables, an interesting question is how it will be affected if we control for another variable(s), where control means hold constant.
R offers the function pcor.test() in the ppcor package. This function has the format pcor.test(X,Y,Z) where X and Y are the variables for which we want to compute the correlation, while Z consists of column vectors containing the controlling variable(s).
In the link below, we apply pcor.test() to a dataset and compare it will computing correlations by group. The results show that computing correlations by group, provides useful insights, while pcor.test() does not.
Theo's Data Science Blog 