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The agreement chart
BACKGROUND: When assessing the concordance between two methods of measurement of ordinal categorical data, summary measures such as Cohen’s (1960) kappa or Bangdiwala’s (1985) B-statistic are used. However, a picture conveys more information than a single summary measure. METHODS: We describe how to...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733724/ https://www.ncbi.nlm.nih.gov/pubmed/23890315 http://dx.doi.org/10.1186/1471-2288-13-97 |
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author | Bangdiwala, Shrikant I Shankar, Viswanathan |
author_facet | Bangdiwala, Shrikant I Shankar, Viswanathan |
author_sort | Bangdiwala, Shrikant I |
collection | PubMed |
description | BACKGROUND: When assessing the concordance between two methods of measurement of ordinal categorical data, summary measures such as Cohen’s (1960) kappa or Bangdiwala’s (1985) B-statistic are used. However, a picture conveys more information than a single summary measure. METHODS: We describe how to construct and interpret Bangdiwala’s (1985) agreement chart and illustrate its use in visually assessing concordance in several example clinical applications. RESULTS: The agreement charts provide a visual impression that no summary statistic can convey, and summary statistics reduce the information to a single characteristic of the data. However, the visual impression is personal and subjective, and not usually reproducible from one reader to another. CONCLUSIONS: The agreement chart should be used to complement the summary kappa or B-statistics, not to replace them. The graphs can be very helpful to researchers as an early step to understand relationships in their data when assessing concordance. |
format | Online Article Text |
id | pubmed-3733724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37337242013-08-06 The agreement chart Bangdiwala, Shrikant I Shankar, Viswanathan BMC Med Res Methodol Technical Advance BACKGROUND: When assessing the concordance between two methods of measurement of ordinal categorical data, summary measures such as Cohen’s (1960) kappa or Bangdiwala’s (1985) B-statistic are used. However, a picture conveys more information than a single summary measure. METHODS: We describe how to construct and interpret Bangdiwala’s (1985) agreement chart and illustrate its use in visually assessing concordance in several example clinical applications. RESULTS: The agreement charts provide a visual impression that no summary statistic can convey, and summary statistics reduce the information to a single characteristic of the data. However, the visual impression is personal and subjective, and not usually reproducible from one reader to another. CONCLUSIONS: The agreement chart should be used to complement the summary kappa or B-statistics, not to replace them. The graphs can be very helpful to researchers as an early step to understand relationships in their data when assessing concordance. BioMed Central 2013-07-29 /pmc/articles/PMC3733724/ /pubmed/23890315 http://dx.doi.org/10.1186/1471-2288-13-97 Text en Copyright © 2013 Bangdiwala and Shankar; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Advance Bangdiwala, Shrikant I Shankar, Viswanathan The agreement chart |
title | The agreement chart |
title_full | The agreement chart |
title_fullStr | The agreement chart |
title_full_unstemmed | The agreement chart |
title_short | The agreement chart |
title_sort | agreement chart |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733724/ https://www.ncbi.nlm.nih.gov/pubmed/23890315 http://dx.doi.org/10.1186/1471-2288-13-97 |
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