Ladder Rank Salary Data
The salary data for all Ladder Rank Faculty in the School of Law are plotted below.
As a function of rank, step, and gender:
As a function of rank, step, and ethnicity:
Multiple Linear Regression Analysis
Multiple regression analysis of salary vs rank/step. As indicated in Table 1, the simplest model with only demographic variables shows that relative to white male faculty, women earn salaries that are 14.6% lower, Asian faculty 12.1% lower, and URM faculty 11.1% lower. Only 18% of salary variation is explained by this model. After all control factors are added, 73% of salary variation is explained by a model with demographic, experience, field, and rank variables. After adjusting for covariates, relative to white male faculty, salaries are 10.7% lower for faculty who are women, 0.6% higher for Asian, and 11.2% higher for URM faculty. In the final model, Women faculty earning difference is statistically significant determinants of faculty salary. The final model predicted salaries within plus or minus 29.9%. (For technically-minded readers, the RMSE on the log base 10 scale is 0.0569.)
Progression Analysis
The progression data for all Law Ladder Rank Faculty are plotted below.
Progress by gender:
Progress by ethnicity:
Progress Rate Analysis
The school of Law has a unique progression structure that doesn’t lend itself to analyses in the same way as the rest of campus. Future studies will work with key stakeholders in the School of Law to analyze progress in ways that best reflect what normal progress is.