admissions: Data set: Simulated Admissions Data with Binary Outcome
In ledell/cvAUC: Cross-Validated Area Under the ROC Curve Confidence Intervals

This is a simulated data set that represents admissions information for a graduate program in the sciences. The binary outcome is 1 for admitted and 0 for not admitted. This data set is meant to be used with the ci.cvAUC function.

1	data(admissions)

A data frame. The five predictor variables are: quant, verbal, gpa, toptier and research. We can treat quant and verbal, which represent quantitative and verbal GRE scores, as continuous variables. The binary indicator variables, toptier and research, indicate whether the application is coming from a “top tier” institution and whether or not they have prior research experience. The binary indicator, Y, represents admitted (Y=1) vs. not admitted (Y=0).