It probably is easier to use Proc Logistic. You can calculate the point-biserial correlation coefficient for 0/1 coded categorical variable with two categories using the Pearson's method. With respect to continuous variables, it depends on whether your data is 1. normally distributed and 2. likely to have outliers. The following thesis showed that Pearson's can be used for non-normally distributed data, but, because it is sensitive to outliers, Pearson's is not good for datasets where outliers are very likely: Pearson’s, Spearman’s and Kendall’s correlation coefficients are the most commonly used measures of monotone association, with the latter two usually suggestedfor non-normally distributed data. Pearson’s correlation coefficient could offer a substantial improvement in statistical power even for distributions with moderate skewness... Nonetheless, because of its known sensitivity to outliers, Pearson’s correlation leads to a less powerful statistical test for distributions with extreme skewness or excess of kurtosis (where the datasets with outliers are more likely). In conclusion,... Pearson’s correlation coefficient could have significant advantages for continuous non-normal data which does not have obvious outliers. Reference Pearson's vs. Kendall's Correlation for Continuous Data
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