  Graduate admissions committees are slowly ending the use of GRE scores due to
concerns that they restrict access to underrepresented groups but have limited
predictive utility. Similar to previous studies, this analysis uses common
admissions metrics such as undergraduate GPA (UGPA) and GRE scores to predict
PhD completion. Now, using statistical methods recently advocated in causal
inference literature, a counterfactual mediation framework is used to determine
whether these metrics directly predict PhD completion or indirectly predict
completion via an intermediate variable (graduate GPA). Consistent with prior
work, results show that UGPA is a stronger predictor of completion than Physics
GRE scores. However, the analysis reveals that these effects are fully mediated
by graduate GPA, suggesting that admissions metrics are measuring traits linked
to graduate course performance, which in turn affects graduate attrition. Poor
course performance may negatively influence personal factors (e.g.,
self-efficacy, identity), limit access to research opportunities (e.g.,
repeating classes, ease of finding a research lab), or may indicate a lack of
preparation for research, all of which could hinder PhD completion; however,
more research is needed.
