Interpretation of standardized regression coefficients in multiple regression

Abstract

The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for variables in 2,341 two-predictor equations and 8,670 three-predictor equations to examine the information they provided for evaluating variable importance. A subset of 1,316 two-predictor equations lacking suppression and a subset of 1,127 three-predictor equations lacking suppression were also examined. Results show that beta values can be used for interpreting the importance of predictors within an equation, but the interpretation is complex. Caution is required for three or more predictors. It is contended that when evaluating the importance of a variable, it is not wise to use the beta value alone. Thirty-two tables present the results of the analyses. (SLD)