{
  "abstract": "Rare clinical outcomes pose a difficulty deeper than ordinary class imbalance: a penalized logistic model can return finite, stable-looking coefficients before the data support a reliable threshold decision. We formulate the accrual question as decision-targeted sequential certification. On a prespecified finite monitoring schedule and target set, asymptotic prediction bands are adjusted for simultaneous coverage, and certification is assessed only among profiles that might be referred, so that a large low-risk majority cannot trigger an uninformative stop. Under the working rare-event logistic model and stated regularity conditions, each certified decision is asymptotically model-conditionally correct with probability at least \\(1-α\\) over the schedule, and the effective information scales with the number of genuine events. Simulations and a US linked birth/infant-death application illustrate the gap between a model that is merely estimable and one whose decisions are certifiable: the whole-population rule stopped while more than half of referral-relevant profiles remained ambiguous, whereas the decision-targeted rule did not certify by the 300{,}000-birth horizon despite stable temporal validation. Regularization makes a rare-event model estimable but does not substitute for genuine rare-event information.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.01968",
  "author_total": 2,
  "authors": [
    {
      "name": "Hui-Mean Foo"
    },
    {
      "name": "Yuan-chin Ivan Chang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8q9cb4r5zd1es.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.01968",
  "fulltext_url": null,
  "id": "8q9cb4r5zd1es",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.01968",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.AP"
    ],
    [
      "openalex",
      "2613|Statistical Methods in Epidemiology"
    ]
  ],
  "openalex": "W7207619786",
  "pdf_url": "https://arxiv.org/pdf/2609.01968",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-02",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8q9cb4r5zd1es.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:26Z",
      "native_id": "2609.01968",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.01968"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Sequential Certification of Threshold Decisions in Rare-Event Risk Prediction",
  "title_text": "Sequential Certification of Threshold Decisions in Rare-Event Risk Prediction",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:26Z",
  "url": "https://research.draconitic.com/paper/8q9cb4r5zd1es",
  "venue": "arXiv",
  "versions": []
}