Analysis Details

This is a lagging analysis, following students that began in 2012-2013, 2013-2014, 2014-2015. A cohort includes first time freshman and transfer students that begin in a given year, with students starting in the summer counted toward the next fall. Only students that declare a major are counted. Graduation is considered up to current time.

 

All three factors have main effects (via Logistic Regression) and an interaction between race/ethnicity and generation. In other words, being first generation for a represented student raises the probability of not graduating a lot. However, if one is an underrepresented student, the deck is already stacked against you and being first generation does not increase the probability of not graduating as much.

Gender has a uniform effect regardless of generation and race/ethnicity.

## Analysis of Deviance Table (Type II tests)
## 
## Response: cbind(n, total)
##                                  LR Chisq Df Pr(>Chisq)    
## gender                             65.522  1  5.746e-16 ***
## race_ethnicity                     45.845  1  1.280e-11 ***
## generation                         93.282  1  < 2.2e-16 ***
## gender:race_ethnicity               0.858  1    0.35435    
## gender:generation                   2.938  1    0.08649 .  
## race_ethnicity:generation           4.040  1    0.04444 *  
## gender:race_ethnicity:generation    0.027  1    0.86923    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1