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NP-LEAP: Nonparametric Latent Exchangeability Prior for Model-Lean Borrowing from Historical Data — arXiv:2608.16688

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.16688
License (as archived): CC0-1.0
Archived: 2026-10-18T20:05:17.245Z
SHA-256 of the archived text: 8699b6cc0c401fe73242deaa6a4422e39bed67e56fc71d0e4df46673c7d5de6d
Stable URL of this page: https://metraipolis.com/documento/dc_ba28fedb6044

How to cite

NP-LEAP: Nonparametric Latent Exchangeability Prior for Model-Lean Borrowing from Historical Data — arXiv:2608.16688 — arXiv (en), https://arxiv.org/abs/2608.16688 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ba28fedb6044 (Metraipolis archive dc_ba28fedb6044, sha256 8699b6cc0c401fe73242deaa6a4422e39bed67e56fc71d0e4df46673c7d5de6d)

BibTeX

@misc{dcba28fedb6044,
  title = {NP-LEAP: Nonparametric Latent Exchangeability Prior for Model-Lean Borrowing from Historical Data — arXiv:2608.16688},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.16688},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ba28fedb6044; sha256 8699b6cc0c401fe73242deaa6a4422e39bed67e56fc71d0e4df46673c7d5de6d},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.16688. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Bayesian dynamic borrowing (BDB) methods leverage historical data to reduce treatment effect uncertainty, yet existing approaches rely on parametric outcome models susceptible to misspecification. We propose the nonparametric latent exchangeability prior (NP-LEAP), an outcome-agnostic, assumption-lean framework to borrow information from historical data. The NP-LEAP performs individual-level exchangeability assessment, inducing Bayesian model averaging over all possible partitions of the historical data into exchangeable and nonexchangeable subsets. Although applicable to a variety of data types with choice of appropriate kernel, the NP-LEAP is particularly well-suited for studies with time-to-event outcomes, where parametric BDB is potentially triply misspecified - imposing a parametric baseline hazard, the proportional hazards structure, and blanket exchangeability. We establish posterior consistency under mild regularity conditions. Simulation studies demonstrate favorable operating characteristics relative to parametric borrowing methods and nonborrowing semiparametric frequentist methods. We illustrate the method by augmenting the control arm in a randomized trial of patients with non-small cell lung cancer.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-08-18 in stat.ME).
Categorie arXiv: Methodology (stat.ME) ; Applications (stat.AP).
Pagina del lavoro: https://arxiv.org/abs/2608.16688 — 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 2026-10-18T19:44:19.581Z dalla pagina https://arxiv.org/catchup/stat.ME/2026-08-18?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).