The C-index illusion: discrimination without calibration in published survival models
Recent work has argued normatively, on synthetic data, that evaluating survival models by discrimination alone (concordance index) yields systematically misleading model comparisons, because the metric ignores calibration and time-dependent accuracy. Whether this matters for real, published, non-clinical models has not been tested. We reproduce three published survival-ML models across three structurally distinct domains -- hard-drive failure prediction, peer-to-peer credit default, and user disengagement on digital platforms -- validate our instrument against the anchor paper's own synthetic experiment, and test five pre-registered hypotheses under a Holm-corrected family-wise error rate...
| Authors | Rafael da Silva, Danilo Alvares |
|---|---|
| Primary category | cs.LG |
| Published | 21 July 2026 |
| Last updated at source | 11 September 2026 |
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