Table 2.
Model Assessment on Internal Validation Using .632 Bootstrapping With 1,000 Resampled Datasets, n = 1,276
| Metric | Area under the Curve |
Calibration Slope | Calibration Intercept | Brier Score | |
|---|---|---|---|---|---|
| Apparent | Internal Validation | ||||
| GLM | .697 (.695-.701) | .678 (.676-.680) | .932 (.920-.943) | .01 (.008-.012) | .12 (.107-.133) |
| Elastic net | .684 (.680-.687) | .664 (.662-.666) | .993 (.981-1.005) | .001 (−.001-.003) | .188 (.179-.197) |
| Random forest | .835 (.831-.839) | .707 (.704-.710) | 1.03 (1.02-1.04) | −.004 (−.006-.003) | .107 (.095-.119) |
| XGBoost | .824 (.819-.827) | .708 (.702-.720) | 1.01 (1.003-1.02) | −.001 (−.003-0) | .106 (.093-.118) |
| Adaptive boost | .827 (.823-.831) | .725 (.723-.727) | 1.056 (1.049-1.063) | −.008 (−.01-.007) | .107 (.095-.12) |
| Ensemble | .850 (.846-.854) | .709 (.710-.712) | .993 (.981-1.005) | .001 (−.001-.003) | .068 (.057-.079) |
GLM, generalized linear model. Null model Brier score = .085.