Survival of the fittest Cox model: Pivotal variable selection for time-to-event data

Maxime van Cutsem; Sylvain Sardy

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arXiv · 2510.19374

Survival of the fittest Cox model: Pivotal variable selection for time-to-event data

Maxime van Cutsem·Sylvain Sardy

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Abstract

We revisit Cox's proportional hazards model to improve variable selection in survival analysis. A square-root transformation of the partial likelihood renders the selection of the regularization parameter pivotal, free of the unknown baseline hazard and censoring mechanism. The resulting criterion borrows from information criteria such as BIC and from penalized regression methods such as the lasso, taking the best of both. On simulated and real data, our method substantially improves upon state-of-the-art approaches used daily in support recovery.

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Maxime van Cutsem, Sylvain Sardy. 2025-10-22. Survival of the fittest Cox model: Pivotal variable selection for time-to-event data. https://arxiv.org/abs/2510.19374

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