ArticleStatistical methods in medical research2018
A measure of association for ordered categorical data in population-based studies.
Article in Statistical methods in medical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Fire Acupuncture versus conventional acupuncture to treat spasticity after stroke: A systematic review and meta-analysis.PloS one · 2021Pooled it
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- Periodontal soft tissue increase induced by periodontally accelerated osteogenic orthodontics surgery.BMC oral health · 2022Article
- Persistent inter-observer variability of breast density assessment using BI-RADS® 5th edition guidelines.Clinical imaging · 2022Article
- Variability in grading of ductal carcinoma in situ among an international group of pathologists.The journal of pathology. Clinical research · 2021Article
- Sickle cell disease mice have cerebral oxidative stress and vascular and white matter abnormalities.Blood cells, molecules & diseases · 2021Article
- Methods of assessing categorical agreement between correlated screening tests in clinical studies.Journal of applied statistics · 2021Article
- Measuring intrarater association between correlated ordinal ratings.Biometrical journal. Biometrische Zeitschrift · 2020Article
- Risk of bias and reporting completeness of randomised controlled trials in burn care: protocol for a systematic review.BMJ open · 2019Article
- Summary measures of agreement and association between many raters' ordinal classifications.Annals of epidemiology · 2017Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Ordinal classification scales are commonly used to define a patient's disease status in screening and diagnostic tests such as mammography. Challenges arise in agreement studies when evaluating the association between many raters' classifications of patients' disease or health status when an ordered categorical scale is used. In this paper, we describe a population-based approach and chance-corrected measure of association to evaluate the strength of relationship between multiple raters' ordinal classifications where any number of raters can be accommodated. In contrast to Shrout and Fleiss' intraclass correlation coefficient, the proposed measure of association is invariant with respect to changes in disease prevalence. We demonstrate how unique characteristics of individual raters can be explored using random effects. Simulation studies are conducted to demonstrate the properties of the proposed method under varying assumptions. The methods are applied to two large-scale agreement studies of breast cancer screening and prostate cancer severity.
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Registered trials
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