{
  "abstract": "This paper studies adaptive experimental design for multiple testing, where an experimenter sequentially chooses which hypothesis to sample. We propose the e-value-based posterior sampling (e-PS) procedure, which uses the empirical average of log e-value increments to guide randomized sampling and applies e-BH to construct rejection sets. Under conditionally valid e-value increments, the procedure controls the false discovery rate at arbitrary stopping times and produces nested rejection sets. We establish high-probability bounds on the number of samples needed to discover all nonnull hypotheses in terms of the growth and concentration of the underlying e-processes. We specialize these bounds to simple-versus-simple, composite-versus-simple, and simple-versus-composite testing. Simulations and experiments using joke ratings and watermarked text illustrate the procedure's power under limited sampling budgets.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.26651",
  "author_total": 4,
  "authors": [
    {
      "name": "Zhanran Lin"
    },
    {
      "name": "Wanteng Ma"
    },
    {
      "name": "Zhimei Ren"
    },
    {
      "name": "Yuting Wei"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c00vk0wv6cc3g.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.26651",
  "fulltext_url": null,
  "id": "c00vk0wv6cc3g",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.26651",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "openalex",
      "2613|Statistical Methods in Clinical Trials"
    ]
  ],
  "openalex": "W7214128849",
  "pdf_url": "https://arxiv.org/pdf/2609.26651",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-22",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/c00vk0wv6cc3g.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:49Z",
      "native_id": "2609.26651",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.26651"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ME",
      "subfield": "statistics"
    }
  ],
  "title": "Sample-Efficient Multiple Testing with Adaptive Data Collection",
  "title_text": "Sample-Efficient Multiple Testing with Adaptive Data Collection",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:49Z",
  "url": "https://research.draconitic.com/paper/c00vk0wv6cc3g",
  "venue": "arXiv",
  "versions": []
}