Interpreting Regression Effects
Description
The purpose of this package is to provide methods to interpret multiple
linear regression and canonical correlation results including beta weights,structure coefficients,
validity coefficients, product measures, relative weights, all-possible-subsets regression,
dominance analysis, commonality analysis, and adjusted effect sizes.