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An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters

The Bland–Altman plot is the most common method to analyze and visualize agreement between raters or methods of quantitative outcomes in health research. While very useful for studies with two raters, a limitation of the classical Bland–Altman plot is that it is specifically used for studies with tw...

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Autores principales: Möller, Sören, Debrabant, Birgit, Halekoh, Ulrich, Petersen, Andreas Kristian, Gerke, Oke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7824071/
https://www.ncbi.nlm.nih.gov/pubmed/33401454
http://dx.doi.org/10.3390/diagnostics11010054
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author Möller, Sören
Debrabant, Birgit
Halekoh, Ulrich
Petersen, Andreas Kristian
Gerke, Oke
author_facet Möller, Sören
Debrabant, Birgit
Halekoh, Ulrich
Petersen, Andreas Kristian
Gerke, Oke
author_sort Möller, Sören
collection PubMed
description The Bland–Altman plot is the most common method to analyze and visualize agreement between raters or methods of quantitative outcomes in health research. While very useful for studies with two raters, a limitation of the classical Bland–Altman plot is that it is specifically used for studies with two raters. We propose an extension of the Bland–Altman plot suitable for more than two raters and derive the approximate limits of agreement with [Formula: see text] confidence intervals. We validated the suggested limit of agreement by a simulation study. Moreover, we offer suggestions on how to present bias, heterogeneity among raters, as well as the uncertainty of the limits of agreement. The resulting plot could be utilized to investigate and present agreement in studies with more than two raters.
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spelling pubmed-78240712021-01-24 An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters Möller, Sören Debrabant, Birgit Halekoh, Ulrich Petersen, Andreas Kristian Gerke, Oke Diagnostics (Basel) Article The Bland–Altman plot is the most common method to analyze and visualize agreement between raters or methods of quantitative outcomes in health research. While very useful for studies with two raters, a limitation of the classical Bland–Altman plot is that it is specifically used for studies with two raters. We propose an extension of the Bland–Altman plot suitable for more than two raters and derive the approximate limits of agreement with [Formula: see text] confidence intervals. We validated the suggested limit of agreement by a simulation study. Moreover, we offer suggestions on how to present bias, heterogeneity among raters, as well as the uncertainty of the limits of agreement. The resulting plot could be utilized to investigate and present agreement in studies with more than two raters. MDPI 2021-01-01 /pmc/articles/PMC7824071/ /pubmed/33401454 http://dx.doi.org/10.3390/diagnostics11010054 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Möller, Sören
Debrabant, Birgit
Halekoh, Ulrich
Petersen, Andreas Kristian
Gerke, Oke
An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters
title An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters
title_full An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters
title_fullStr An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters
title_full_unstemmed An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters
title_short An Extension of the Bland–Altman Plot for Analyzing the Agreement of More than Two Raters
title_sort extension of the bland–altman plot for analyzing the agreement of more than two raters
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7824071/
https://www.ncbi.nlm.nih.gov/pubmed/33401454
http://dx.doi.org/10.3390/diagnostics11010054
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