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Kappa statistic to measure agreement beyond chance in free-response assessments

BACKGROUND: The usual kappa statistic requires that all observations be enumerated. However, in free-response assessments, only positive (or abnormal) findings are notified, but negative (or normal) findings are not. This situation occurs frequently in imaging or other diagnostic studies. We propose...

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Autores principales: Carpentier, Marc, Combescure, Christophe, Merlini, Laura, Perneger, Thomas V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395923/
https://www.ncbi.nlm.nih.gov/pubmed/28420347
http://dx.doi.org/10.1186/s12874-017-0340-6
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author Carpentier, Marc
Combescure, Christophe
Merlini, Laura
Perneger, Thomas V.
author_facet Carpentier, Marc
Combescure, Christophe
Merlini, Laura
Perneger, Thomas V.
author_sort Carpentier, Marc
collection PubMed
description BACKGROUND: The usual kappa statistic requires that all observations be enumerated. However, in free-response assessments, only positive (or abnormal) findings are notified, but negative (or normal) findings are not. This situation occurs frequently in imaging or other diagnostic studies. We propose here a kappa statistic that is suitable for free-response assessments. METHOD: We derived the equivalent of Cohen’s kappa statistic for two raters under the assumption that the number of possible findings for any given patient is very large, as well as a formula for sampling variance that is applicable to independent observations (for clustered observations, a bootstrap procedure is proposed). The proposed statistic was applied to a real-life dataset, and compared with the common practice of collapsing observations within a finite number of regions of interest. RESULTS: The free-response kappa is computed from the total numbers of discordant (b and c) and concordant positive (d) observations made in all patients, as 2d/(b + c + 2d). In 84 full-body magnetic resonance imaging procedures in children that were evaluated by 2 independent raters, the free-response kappa statistic was 0.820. Aggregation of results within regions of interest resulted in overestimation of agreement beyond chance. CONCLUSIONS: The free-response kappa provides an estimate of agreement beyond chance in situations where only positive findings are reported by raters.
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spelling pubmed-53959232017-04-20 Kappa statistic to measure agreement beyond chance in free-response assessments Carpentier, Marc Combescure, Christophe Merlini, Laura Perneger, Thomas V. BMC Med Res Methodol Research Article BACKGROUND: The usual kappa statistic requires that all observations be enumerated. However, in free-response assessments, only positive (or abnormal) findings are notified, but negative (or normal) findings are not. This situation occurs frequently in imaging or other diagnostic studies. We propose here a kappa statistic that is suitable for free-response assessments. METHOD: We derived the equivalent of Cohen’s kappa statistic for two raters under the assumption that the number of possible findings for any given patient is very large, as well as a formula for sampling variance that is applicable to independent observations (for clustered observations, a bootstrap procedure is proposed). The proposed statistic was applied to a real-life dataset, and compared with the common practice of collapsing observations within a finite number of regions of interest. RESULTS: The free-response kappa is computed from the total numbers of discordant (b and c) and concordant positive (d) observations made in all patients, as 2d/(b + c + 2d). In 84 full-body magnetic resonance imaging procedures in children that were evaluated by 2 independent raters, the free-response kappa statistic was 0.820. Aggregation of results within regions of interest resulted in overestimation of agreement beyond chance. CONCLUSIONS: The free-response kappa provides an estimate of agreement beyond chance in situations where only positive findings are reported by raters. BioMed Central 2017-04-19 /pmc/articles/PMC5395923/ /pubmed/28420347 http://dx.doi.org/10.1186/s12874-017-0340-6 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Carpentier, Marc
Combescure, Christophe
Merlini, Laura
Perneger, Thomas V.
Kappa statistic to measure agreement beyond chance in free-response assessments
title Kappa statistic to measure agreement beyond chance in free-response assessments
title_full Kappa statistic to measure agreement beyond chance in free-response assessments
title_fullStr Kappa statistic to measure agreement beyond chance in free-response assessments
title_full_unstemmed Kappa statistic to measure agreement beyond chance in free-response assessments
title_short Kappa statistic to measure agreement beyond chance in free-response assessments
title_sort kappa statistic to measure agreement beyond chance in free-response assessments
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5395923/
https://www.ncbi.nlm.nih.gov/pubmed/28420347
http://dx.doi.org/10.1186/s12874-017-0340-6
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