Salary Equity: Similarities and Differences in Outcomes From Two Common Prediction Models

Abstract

Stepwise multiple regression was used to develop salary prediction equations, one from each of the two faculty samples most frequently utilized in this type of research (males only, all faculty). These equations were developed using faculty information from an American Association of University Professors (AAUP) Category I institution showing typical sex-difference patterns in salary and other professional characteristics. Sex did not enter into the all-faculty equation. However, an analysis model using residuals showed that women, on the average, were paid significantly less than men. This sex difference was larger using the male, rather than the all-faculty, sample. Higher percentages of males than females were both overpaid and underpaid. Efficacy of the analysis model and differences in results from the two salary prediction equations are discussed.