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Asymptotic variability of (multilevel) multirater kappa coefficients

Agreement studies are of paramount importance in various scientific domains. When several observers classify objects on categorical scales, agreement can be quantified through multirater kappa coefficients. In most statistical packages, the standard error of these coefficients is only available unde...

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Detalles Bibliográficos
Autor principal: Vanbelle, Sophie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6745615/
https://www.ncbi.nlm.nih.gov/pubmed/30132375
http://dx.doi.org/10.1177/0962280218794733
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author Vanbelle, Sophie
author_facet Vanbelle, Sophie
author_sort Vanbelle, Sophie
collection PubMed
description Agreement studies are of paramount importance in various scientific domains. When several observers classify objects on categorical scales, agreement can be quantified through multirater kappa coefficients. In most statistical packages, the standard error of these coefficients is only available under the null hypothesis that the coefficient is equal to zero, preventing the construction of confidence intervals in the general case. The aim of this paper is triple. First, simple analytic formulae for the standard error of multirater kappa coefficients will be given in the general case. Second, these formulae will be extended to the case of multilevel data structures. The formulae are based on simple matrix algebra and are implemented in the R package “multiagree”. Third, guidelines on the choice between the different mulitrater kappa coefficients will be provided.
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spelling pubmed-67456152019-10-03 Asymptotic variability of (multilevel) multirater kappa coefficients Vanbelle, Sophie Stat Methods Med Res Articles Agreement studies are of paramount importance in various scientific domains. When several observers classify objects on categorical scales, agreement can be quantified through multirater kappa coefficients. In most statistical packages, the standard error of these coefficients is only available under the null hypothesis that the coefficient is equal to zero, preventing the construction of confidence intervals in the general case. The aim of this paper is triple. First, simple analytic formulae for the standard error of multirater kappa coefficients will be given in the general case. Second, these formulae will be extended to the case of multilevel data structures. The formulae are based on simple matrix algebra and are implemented in the R package “multiagree”. Third, guidelines on the choice between the different mulitrater kappa coefficients will be provided. SAGE Publications 2018-08-22 2019-11 /pmc/articles/PMC6745615/ /pubmed/30132375 http://dx.doi.org/10.1177/0962280218794733 Text en © The Author(s) 2018 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Articles
Vanbelle, Sophie
Asymptotic variability of (multilevel) multirater kappa coefficients
title Asymptotic variability of (multilevel) multirater kappa coefficients
title_full Asymptotic variability of (multilevel) multirater kappa coefficients
title_fullStr Asymptotic variability of (multilevel) multirater kappa coefficients
title_full_unstemmed Asymptotic variability of (multilevel) multirater kappa coefficients
title_short Asymptotic variability of (multilevel) multirater kappa coefficients
title_sort asymptotic variability of (multilevel) multirater kappa coefficients
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6745615/
https://www.ncbi.nlm.nih.gov/pubmed/30132375
http://dx.doi.org/10.1177/0962280218794733
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