Data for generating ROC curve.
Examples
model <- glm(honcomp ~ female + read + science, data = hsb2,
family = binomial(link = 'logit'))
gt <- blr_gains_table(model)
blr_prep_roc_data(gt)
#> sensitivity specificity sensitivity_per 1 - specificity
#> 1 NA NA 0.0000000 0.00000000
#> 2 26.41509 95.91837 0.2641509 0.04081633
#> 3 50.94340 91.15646 0.5094340 0.08843537
#> 4 69.81132 84.35374 0.6981132 0.15646259
#> 5 83.01887 75.51020 0.8301887 0.24489796
#> 6 88.67925 63.94558 0.8867925 0.36054422
#> 7 94.33962 52.38095 0.9433962 0.47619048
#> 8 96.22642 39.45578 0.9622642 0.60544218
#> 9 100.00000 27.21088 1.0000000 0.72789116
#> 10 100.00000 13.60544 1.0000000 0.86394558
#> 11 100.00000 0.00000 1.0000000 1.00000000