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Creators/Authors contains: "Posselt, Julie R."

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  1. We provide statistical measures and additional analyses showing that our original analyses were sound. We use a generalized linear mixed model to account for program-to-program differences with program as a random effect without stratifying with tier and found the GRE-P (Graduate Record Examination physics test) effect is not different from our previous findings, thereby alleviating concern of collider bias. Variance inflation factors for each variable were low, showing that multicollinearity was not a concern. We show that range restriction is not an issue for GRE-P or GRE-V (GRE verbal), and only a minor issue for GRE-Q (GRE quantitative). Last, we use statistical measures of model quality to show that our published models are better than or equivalent to several alternates.
  2. This study aims to understand the effectiveness of typical admissions criteria in identifying students who will complete the Physics Ph.D. Multivariate statistical analysis of roughly one in eight physics Ph.D. students from 2000 to 2010 indicates that the traditional admissions metrics of undergraduate grade point average (GPA) and the Graduate Record Examination (GRE) Quantitative, Verbal, and Physics Subject Tests do not predict completion as effectively admissions committees presume. Significant associations with completion were found for undergraduate GPA in all models and for GRE Quantitative in two of four studied models; GRE Physics and GRE Verbal were not significant in any model. It is notable that completion changed by less than 10% for U.S. physics major test takers scoring in the 10th versus 90th percentile on the Quantitative test. Aside from these limitations in predicting Ph.D. completion overall, overreliance on GRE scores in admissions processes also selects against underrepresented groups.