Survival Analysis

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Period ending 2026-09-21

1 new paper

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Period ending 2026-09-07

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63 papers

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Survival of the fittest Cox model: Pivotal variable selection for time-to-event data
Oct 22, 2025Maxime van Cutsem, Sylvain SardyTime-To-Event Data Survival Analysis
Overcoming Dependent Censoring in the Evaluation of Survival Models
Feb 26, 2025Christian Marius Lillelund, Shi-ang Qi, Russell GreinerSurvival Analysis Gaussian Copula
The C-index illusion: discrimination without calibration in published survival models
Date pendingRafael da Silva, Danilo AlvaresSurvival Predictions Survival Analysis

Oct 22, 2025 · stat.MLJ/K move · Enter open · S save

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

Maxime van Cutsem, Sylvain Sardy

Department of Mathematics, University of Geneva

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.

Time-To-Event Data Survival Analysis Model Selection Lasso Likelihood

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