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Bayes factor testing of equality and order constraints on measures of association in social research
Measures of association play a central role in the social sciences to quantify the strength of a linear relationship between the variables of interest. In many applications researchers can translate scientific expectations to hypotheses with equality and/or order constraints on these measures of ass...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870006/ https://www.ncbi.nlm.nih.gov/pubmed/36698541 http://dx.doi.org/10.1080/02664763.2021.1992360 |
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author | Mulder, Joris Gelissen, John P. T. M. |
author_facet | Mulder, Joris Gelissen, John P. T. M. |
author_sort | Mulder, Joris |
collection | PubMed |
description | Measures of association play a central role in the social sciences to quantify the strength of a linear relationship between the variables of interest. In many applications researchers can translate scientific expectations to hypotheses with equality and/or order constraints on these measures of association. In this paper a Bayes factor test is proposed for testing multiple hypotheses with constraints on the measures of association between ordinal and/or continuous variables, possibly after correcting for certain covariates. This test can be used to obtain a direct answer to the research question how much evidence there is in the data for a social science theory relative to competing theories. The stand-alone software package ‘BCT’ allows users to apply the methodology in an easy manner. The methodology will also be available in the R package ‘BFpack’. An empirical application from leisure studies about the associations between life, leisure and relationship satisfaction and an application about the differences about egalitarian justice beliefs across countries are used to illustrate the methodology. |
format | Online Article Text |
id | pubmed-9870006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-98700062023-01-24 Bayes factor testing of equality and order constraints on measures of association in social research Mulder, Joris Gelissen, John P. T. M. J Appl Stat Articles Measures of association play a central role in the social sciences to quantify the strength of a linear relationship between the variables of interest. In many applications researchers can translate scientific expectations to hypotheses with equality and/or order constraints on these measures of association. In this paper a Bayes factor test is proposed for testing multiple hypotheses with constraints on the measures of association between ordinal and/or continuous variables, possibly after correcting for certain covariates. This test can be used to obtain a direct answer to the research question how much evidence there is in the data for a social science theory relative to competing theories. The stand-alone software package ‘BCT’ allows users to apply the methodology in an easy manner. The methodology will also be available in the R package ‘BFpack’. An empirical application from leisure studies about the associations between life, leisure and relationship satisfaction and an application about the differences about egalitarian justice beliefs across countries are used to illustrate the methodology. Taylor & Francis 2021-10-27 /pmc/articles/PMC9870006/ /pubmed/36698541 http://dx.doi.org/10.1080/02664763.2021.1992360 Text en © 2021 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 Mulder, Joris Gelissen, John P. T. M. Bayes factor testing of equality and order constraints on measures of association in social research |
title | Bayes factor testing of equality and order constraints on measures of association in social research |
title_full | Bayes factor testing of equality and order constraints on measures of association in social research |
title_fullStr | Bayes factor testing of equality and order constraints on measures of association in social research |
title_full_unstemmed | Bayes factor testing of equality and order constraints on measures of association in social research |
title_short | Bayes factor testing of equality and order constraints on measures of association in social research |
title_sort | bayes factor testing of equality and order constraints on measures of association in social research |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9870006/ https://www.ncbi.nlm.nih.gov/pubmed/36698541 http://dx.doi.org/10.1080/02664763.2021.1992360 |
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