{
  "abstract": "In survival studies, right censoring often prevents the observation of subjects' complete outcomes, complicating inference about the underlying distribution. Evaluating whether a given distribution adequately fits right-censored data is therefore essential. However, guidance on the relative performance of available goodness-of-fit tests under different data conditions remains limited. In this work, we present a comparative assessment of three classical goodness-of-fit tests adapted for right-censored data: Kolmogorov-Smirnov, Anderson-Darling, and Cramér-von Mises. Through an extensive simulation study, we investigate how factors such as the proportion of right-censored observations, sample size, and distributional symmetry influence the statistical power of each test. All procedures were implemented using the R package GofCens, and power estimates were obtained from extensive replicated simulations. The results identify the settings in which each test exhibits superior performance, providing practical, evidence-based recommendations for test selection in survival analysis. These recommendations are summarized as user-oriented guidelines and complemented by a concise graphical cheat sheet, enabling practitioners to quickly identify the most suitable test for their specific application.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.37513",
  "author_total": 3,
  "authors": [
    {
      "name": "Arnau Gómez-Català"
    },
    {
      "name": "Guadalupe Gómez Melis"
    },
    {
      "name": "Klaus Langohr"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4awsbvpmmar45.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.37513",
  "fulltext_url": null,
  "id": "4awsbvpmmar45",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.37513",
  "language": null,
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.AP"
    ],
    [
      "arxiv",
      "stat.ME"
    ],
    [
      "openalex",
      "2613|Statistical Distribution Estimation and Applications"
    ]
  ],
  "openalex": "W7224126147",
  "pdf_url": "https://arxiv.org/pdf/2610.37513",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4awsbvpmmar45.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:35:59Z",
      "native_id": "2610.37513",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.37513"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Practical Guidelines for Goodness-of-Fit Testing for Right-Censored Data",
  "title_text": "Practical Guidelines for Goodness-of-Fit Testing for Right-Censored Data",
  "type": "preprint",
  "updated_at": "2026-10-30T12:35:59Z",
  "url": "https://research.draconitic.com/paper/4awsbvpmmar45",
  "venue": "arXiv",
  "versions": []
}