{
  "abstract": "Generalizability theory (GT) provides a variety of intraclass correlation coefficients (ICCs) to quantify reliability across different conditions of measurement-for example, scale and interrater reliability quantify generalization across items and raters, respectively. In a multilevel modelling (MLM) context, an ICC is often used to quantify the proportion of a subject-level variable's variance that is attributable to cluster-level differences (e.g., between schools or neighbourhoods). When data from cluster members are their ratings of a group-level characteristic, the ICC is an inter-rater reliability coefficient, interpreted as the degree to which observations of a cluster generalize across members of that cluster. Structural equation modelling (SEM) is becoming a popular framework for modelling GT, and the 'omega' indices of composite reliability-which are functions of SEM parameters-are special cases of GT (i.e., how measurements of a construct generalize across indicators). The merger of MLM and SEM (i.e., ML-SEM) provides a unique opportunity to explore how well measurements of cluster-level constructs generalize across multiple measurement conditions (indicators, cluster members, or both). A taxonomy of ICCs is explicated to appropriately quantify reliability across aspects of a procedure for measuring cluster-level constructs, adding value to the limited ICCs currently considered in ML-SEM applications.",
  "abstract_shown": true,
  "affiliations": [
    "University of Amsterdam, Amsterdam, The Netherlands."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Terrence D Jorgensen",
      "orcid": "0000-0001-5111-6773"
    },
    {
      "affs": [
        0
      ],
      "name": "Suzanne Jak",
      "orcid": "0000-0002-2223-5594"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1v9pg86af5vea.bib",
  "cited_by": 1,
  "doi": "10.1111/bmsp.70074",
  "fulltext_url": "https://europepmc.org/articles/PMC13679770",
  "id": "1v9pg86af5vea",
  "issns": [
    "0007-1102",
    "2044-8317"
  ],
  "landing_url": "https://europepmc.org/article/MED/42872674",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1803|Psychometric Methodologies and Testing"
    ]
  ],
  "openalex": "W7211055832",
  "pdf_url": "https://europepmc.org/articles/PMC13679770?pdf=render",
  "pmcid": "PMC13679770",
  "pmid": "42872674",
  "published": "2026-10-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1v9pg86af5vea.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:46Z",
      "native_id": "MED:42872674",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42872674"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "journal-openalex:2613|Statistical Methods and Bayesian Inference",
      "subfield": "statistics"
    }
  ],
  "title": "A taxonomy of reliability indices for cluster-level constructs measured by multiple individual-level indicators.",
  "title_text": "A taxonomy of reliability indices for cluster-level constructs measured by multiple individual-level indicators.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:46Z",
  "url": "https://research.draconitic.com/paper/1v9pg86af5vea",
  "venue": "The British journal of mathematical and statistical psychology",
  "versions": []
}