is used to compensate for the addition of variables to the model. As more independent variables are added to the
regression model, unadjusted R2 will generally increase but there will never be
a decrease. This will occur even when the
additional variables do little to help explain the dependent variable. To compensate for this, adjusted R2 is
corrected for the number of independent variables in the model. The result is an adjusted R2 than can go
up or down depending on whether the addition of another variable adds or does not add to
the explanatory power of the model. Adjusted R2
will always be lower than unadjusted.
become standard practice to report the adjusted R2, especially when there are
multiple models presented with varying numbers of independent variables.