{
  "abstract": "Improving the validity, reliability, and replicability of research in the social and health sciences depends on the quality of measurement. We argue that judging whether the sum score of a multi-item measure adequately represents the intended latent variable rests on four basic criteria — unidimensionality, local independence of items, ordered response categories, and invariance — which can serve as a minimal checklist for end users assessing the quality of a psychometric study. A central recommendation is to stop interpreting model and item fit against rule-of-thumb critical values and instead use simulation-based cutoffs tailored to the data at hand. Because most published psychometric work relies on rule-of-thumb cutoffs, established scales are in urgent need of re-analysis with appropriate methods. We provide an up-to-date overview of methods for evaluating each criterion within Rasch Measurement Theory, point to freely available software that makes these methods accessible, and note outdated approaches to avoid. A draft reporting guideline is provided, as we believe that a consensus-based reporting standard may facilitate more transparent evaluations of scales. Finally, we argue for a higher bar for calling a measure \"valid and reliable\": the existence of an original validation paper, often old and based on outdated methods, is not in itself sufficient evidence of validity.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "name": "Magnus Johansson"
    },
    {
      "name": "Marit Preuter"
    },
    {
      "name": "Jeanette Melin"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dshn1ga6fh6s3.bib",
  "cited_by": 0,
  "doi": "10.31219/osf.io/3htzc_v2",
  "fulltext_url": null,
  "id": "dshn1ga6fh6s3",
  "issns": [],
  "landing_url": "https://osf.io/3htzc_v2/",
  "language": null,
  "licence": "CC0-1.0",
  "licence_label": "CC0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/publicdomain/zero/1.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Life Sciences"
    ],
    [
      "bepress",
      "Social and Behavioral Sciences"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://osf.io/3htzc/download",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dshn1ga6fh6s3.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:26:57Z",
      "native_id": "3htzc",
      "source": "osf",
      "url": "https://osf.io/3htzc_v1/"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "bepress:Life Sciences",
      "subfield": "general"
    }
  ],
  "title": "Valid and Reliable? Basic and Expanded Recommendations for Psychometric Reporting and Quality Assessment",
  "title_text": "Valid and Reliable? Basic and Expanded Recommendations for Psychometric Reporting and Quality Assessment",
  "type": "preprint",
  "updated_at": "2026-10-30T12:26:57Z",
  "url": "https://research.draconitic.com/paper/dshn1ga6fh6s3",
  "venue": "OSF Preprints",
  "versions": []
}