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Selection instability and coefficient uncertainty in Cox modelling after Lasso selection — arXiv:2611.04765

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.04765
License (as archived): CC0-1.0
Archived: 2026-11-04T18:58:07.244Z
SHA-256 of the archived text: 5b3cc58e935f659e1de2dba5fe19ae3ab5fd2dd6b5d0c5ade444d537c2f02561
Stable URL of this page: https://metraipolis.com/documento/dc_ef115fc50cb7

How to cite

Selection instability and coefficient uncertainty in Cox modelling after Lasso selection — arXiv:2611.04765 — arXiv (en), https://arxiv.org/abs/2611.04765 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ef115fc50cb7 (Metraipolis archive dc_ef115fc50cb7, sha256 5b3cc58e935f659e1de2dba5fe19ae3ab5fd2dd6b5d0c5ade444d537c2f02561)

BibTeX

@misc{dcef115fc50cb7,
  title = {Selection instability and coefficient uncertainty in Cox modelling after Lasso selection — arXiv:2611.04765},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.04765},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ef115fc50cb7; sha256 5b3cc58e935f659e1de2dba5fe19ae3ab5fd2dd6b5d0c5ade444d537c2f02561},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.04765. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

After variable selection, uncertainty quantification often treats the selected model as fixed, although it may change under repeated sampling. We investigate whether this variability can be incorporated by repeating Cox-Lasso selection within a model-based bootstrap after unpenalised Cox refitting. We compare conventional post-selection Cox Wald intervals and a model-based bootstrap without re-selection, both of which keep the selected predictor set fixed, with two re-selection procedures: one retains the observed tuning-parameter value, whereas the other reapplies the cross-validation minimum (CV-min) tuning rule within each bootstrap sample. Against the data-generating coefficients, procedures holding the selected predictor set fixed frequently showed substantial undercoverage. Re-selection generally moved coverage closer to the nominal level, although performance varied across simulation regimes and coefficients. Sensitivity analyses evaluating coverage against the population Cox coefficients corresponding to each originally selected predictor set gave similar aggregate coverage for the primary interval comparison. In the NKI70 breast-cancer data, the four selected genes appeared together in only 0.6% of bootstrap samples under re-selection at the observed tuning-parameter value. These results suggest that selection instability can be an important component of post-selection coefficient uncertainty and that bootstrap re-selection can help incorporate this variability.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv stat.ME, nuovi lavori del giorno).
Categorie arXiv: Methodology (stat.ME) ; Computation (stat.CO).
Pagina del lavoro: https://arxiv.org/abs/2611.04765 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-04T18:36:37.176Z dalla pagina https://arxiv.org/list/stat.ME/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).