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Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ

Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood function. This hurdle can be overcome by assuming a latent normal representation that is consistent with the ordinal information in the data: the observed ranks are conceptualized as an impoverished ref...

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Detalles Bibliográficos
Autores principales: van Doorn, J., Ly, A., Marsman, M., Wagenmakers, E.-J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041780/
https://www.ncbi.nlm.nih.gov/pubmed/35707708
http://dx.doi.org/10.1080/02664763.2019.1709053
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author van Doorn, J.
Ly, A.
Marsman, M.
Wagenmakers, E.-J.
author_facet van Doorn, J.
Ly, A.
Marsman, M.
Wagenmakers, E.-J.
author_sort van Doorn, J.
collection PubMed
description Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood function. This hurdle can be overcome by assuming a latent normal representation that is consistent with the ordinal information in the data: the observed ranks are conceptualized as an impoverished reflection of an underlying continuous scale, and inference concerns the parameters that govern the latent representation. We apply this generic data-augmentation method to obtain Bayes factors for three popular rank-based tests: the rank sum test, the signed rank test, and Spearman's [Image: see text] .
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spelling pubmed-90417802022-06-14 Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ van Doorn, J. Ly, A. Marsman, M. Wagenmakers, E.-J. J Appl Stat Articles Bayesian inference for rank-order problems is frustrated by the absence of an explicit likelihood function. This hurdle can be overcome by assuming a latent normal representation that is consistent with the ordinal information in the data: the observed ranks are conceptualized as an impoverished reflection of an underlying continuous scale, and inference concerns the parameters that govern the latent representation. We apply this generic data-augmentation method to obtain Bayes factors for three popular rank-based tests: the rank sum test, the signed rank test, and Spearman's [Image: see text] . Taylor & Francis 2020-01-11 /pmc/articles/PMC9041780/ /pubmed/35707708 http://dx.doi.org/10.1080/02664763.2019.1709053 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
spellingShingle Articles
van Doorn, J.
Ly, A.
Marsman, M.
Wagenmakers, E.-J.
Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
title Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
title_full Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
title_fullStr Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
title_full_unstemmed Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
title_short Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ
title_sort bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and spearman's ρ
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9041780/
https://www.ncbi.nlm.nih.gov/pubmed/35707708
http://dx.doi.org/10.1080/02664763.2019.1709053
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