A regression analysis is the OFCCP’s preferred method of comparing employee salaries to detect if significant differences in pay between gender or race/ethnicity groups exist. PayEval makes conducting a regression analysis simple and straightforward.
“[I]f a contractor performs a multiple regression analysis, which reasonably meets the standards outlined in the voluntary guidelines and the analysis finds no discrimination, OFCCP will consider the contractor’s compensation practices to be in compliance with Executive Order 11246.”
- OFCCP Voluntary Guidelines for Self-Evaluation of Compensation.
The detailed report will include a statistical test of the factors used in the regression model. For this analysis, a table is included with the number of observations used in the analysis, the degrees of freedom for error and the percent of the variation explained by the model. For the overall analysis of gender impacts on compensation, the selected model with the included factors explains 86.5% of the variation in compensation. In the subsequent table, note that service, EEO job code and job title have a significant impact on compensation at a 95% confidence level, as indicated by the highlighted standard deviation values of 5.20, 3.56, and 7.30.
This report also includes significant results from regression across specified categories. For this analysis, we find that there is a significant positive impact in four subgroups based on OFCCP’s guidelines as indicated by the values highlighted in red. Again, however, note that none of these are in qualified comparison groups since there are only 23 employees in the “orange” job group and 21 employees in the “red” job group (based on OFCCP’s 30/5 rule).
Analyses that have no significant regression results will not produce a regression report.
