dc.contributor.author | Mulder, Joris | de |
dc.contributor.author | Gelissen, John P. T. M. | de |
dc.date.accessioned | 2025-02-26T11:49:42Z | |
dc.date.available | 2025-02-26T11:49:42Z | |
dc.date.issued | 2023 | de |
dc.identifier.issn | 1360-0532 | de |
dc.identifier.uri | https://www.ssoar.info/ssoar/handle/document/100373 | |
dc.description.abstract | 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. | de |
dc.language | en | de |
dc.subject.ddc | Sozialwissenschaften, Soziologie | de |
dc.subject.ddc | Social sciences, sociology, anthropology | en |
dc.subject.other | Bayesian hypothesis testing; measures of association; uniform priors; social sciences; BCT; BFpack; EVS 1999 | de |
dc.title | Bayes factor testing of equality and order constraints on measures of association in social research | de |
dc.description.review | begutachtet (peer reviewed) | de |
dc.description.review | peer reviewed | en |
dc.source.journal | Journal of Applied Statistics | |
dc.source.volume | 50 | de |
dc.publisher.country | GBR | de |
dc.source.issue | 2 | de |
dc.subject.classoz | Erhebungstechniken und Analysetechniken der Sozialwissenschaften | de |
dc.subject.classoz | Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods | en |
dc.subject.thesoz | EVS | de |
dc.subject.thesoz | EVS | en |
dc.subject.thesoz | Assoziation | de |
dc.subject.thesoz | association (psych.) | en |
dc.subject.thesoz | Test | de |
dc.subject.thesoz | test | en |
dc.subject.thesoz | Sozialforschung | de |
dc.subject.thesoz | social research | en |
dc.subject.thesoz | Hypothese | de |
dc.subject.thesoz | hypothesis | en |
dc.identifier.urn | urn:nbn:de:0168-ssoar-100373-4 | |
dc.rights.licence | Creative Commons - Namensnennung, Nicht kommerz., Keine Bearbeitung 4.0 | de |
dc.rights.licence | Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0 | en |
ssoar.contributor.institution | FDB | de |
internal.status | formal und inhaltlich fertig erschlossen | de |
internal.identifier.thesoz | 10079761 | |
internal.identifier.thesoz | 10036860 | |
internal.identifier.thesoz | 10037953 | |
internal.identifier.thesoz | 10042041 | |
internal.identifier.thesoz | 10046970 | |
dc.type.stock | article | de |
dc.source.pageinfo | 315-351 | de |
internal.identifier.classoz | 10105 | |
internal.identifier.journal | 2638 | |
internal.identifier.ddc | 300 | |
dc.identifier.doi | https://doi.org/10.1080/02664763.2021.1992360 | de |
dc.description.pubstatus | Veröffentlichungsversion | de |
dc.description.pubstatus | Published Version | en |
internal.identifier.licence | 20 | |
internal.identifier.pubstatus | 1 | |
internal.identifier.review | 1 | |
internal.pdf.valid | false | |
internal.pdf.wellformed | true | |
internal.pdf.encrypted | false | |