The salary data for all Ladder Rank Faculty in the Joe C. Wen School of Population and Public Health are plotted below.

As a function of rank, step, and gender:

Graph 1 salary as a function of rank,step, and gender

As a function of rank, step, and ethnicity:

Graph 2 salary as a function of rank,step, and ethnicity

Multiple Linear Regression Analysis

As indicated in Table 1, the simplest model with only demographic variables shows that relative to white male faculty, women earn salaries that are about 3.4% lower, Asian faculty 2.3% and URM faculty 12.1% lower. The proportion of salary variation explained by this model was 5%. After all control factors are added, 89% 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 about 1.7% higher for faculty who are women, 9.1% lower for Asian, and 13.4% lower for URM faculty. In the final model, Asian faculty earning 9.1% and URM earning 13.4% less than white faculty are statistically significant. The final model predicted salaries within plus or minus 20.8%. (For technically-minded readers, the RMSE on the log base 10 scale is 0.041.)

Table 1 multiple linear regression analysis

Progression Analysis

The progression data for all Population and Public Health Ladder Rank and Professors of Teaching Faculty, are plotted below. Normative progression is defined in the Progression Matrix.

Progress by gender:

graph 3 progress by gender

Progress by ethnicity:

graph 4 progress by ethnicity

Progress Rate Analysis

The results indicate that there is no statistically significant difference in progression rate means by either gender or ethnicity when compared to white male faculty. Normative progression is defined in the Progression Matrix.

Table 2 progress rate in years comparison