(symbol:
R2) a numerical index that reflects the degree to which variation in a response or outcome variable (e.g., workers’ incomes) is accounted for by its relationship with two or more predictor variables (e.g., age, gender, years of education). More specifically, it is a measure of the percentage of variance in a
dependent variable that is accounted for by its relationship with a weighted linear combination of a set of
independent variables. Obtained by multiplying the value of the
multiple correlation coefficient (
R) by itself, the coefficient of multiple determination ranges in value from 0 to 1. Low values indicate that the outcome is relatively unrelated to the predictors, whereas values closer to 1 indicate that the outcome and the predictors are highly related. For example, if
R = .40, then the coefficient of multiple determination is .40
2 = .16 and interpreted to mean 16% of the variance in outcome is explainable by the set of predictors. Also called
multiple correlation coefficient squared;
squared multiple correlation coefficient.