Zitierlink: http://dx.doi.org/10.25819/ubsi/8818
DC ElementWertSprache
crisitem.author.orcid0000-0001-9068-5696-
dc.contributor.authorKelter, Riko-
dc.date.accessioned2021-02-18T09:38:39Z-
dc.date.available2021-02-18T09:38:39Z-
dc.date.issued2020de
dc.descriptionFinanziert aus dem Open-Access-Publikationsfonds der Universität Siegen für Zeitschriftenartikelde
dc.description.abstractTypical situations in research include the comparison of two groups regarding a metric variable, in which case usually the two-sample t-test is applied. While common frequentist two-sample t-tests focus on the difference of means of both groups via a p-value, the quantity of interest in applied research most often is the effect size. Existing Bayesian alternatives of the two-sample t-test replace frequentist significance thresholds like the p-value with the Bayes factor, taking the same testing stance. The R package bayest implements a Markov-Chain-Monte-Carlo algorithm to conduct a Bayesian two-sample t-test which estimates the effect size between two groups, while also providing detailed visualization and analysis of all parameters of interest. Because of its focus on the ease of use and interpretability, clinicians and other users can run this t-test within a few lines of code and find out if differences between two groups are scientifically meaningful, instead of significant.en
dc.identifier.doihttp://dx.doi.org/10.25819/ubsi/8818-
dc.identifier.urihttps://dspace.ub.uni-siegen.de/handle/ubsi/1851-
dc.identifier.urnurn:nbn:de:hbz:467-18511-
dc.language.isoende
dc.sourceJournal of Open Research Software, 8 (1), S.14. - DOI: http://doi.org/10.5334/jors.290de
dc.subject.ddc510 Mathematikde
dc.subject.otherTwo-sample t-testde
dc.subject.otherEffect sizede
dc.subject.otherTreatment effect between two groupsde
dc.subject.otherMarkov-Chain-Monte-Carlode
dc.subject.otherBayesian statisticsde
dc.subject.swbt-Testde
dc.subject.swbA-priori-Verteilungde
dc.subject.swbMarkov-Kettede
dc.subject.swbMonte-Carlo-Simulationde
dc.subject.swbR <Programm>de
dc.titlebayest: an R-package for effect-size targeted Bayesian two-sample t-testsen
dc.typeArticlede
item.fulltextWith Fulltext-
ubsi.origin.dspace51-
ubsi.publication.affiliationDepartment Mathematikde
ubsi.source.issn2049-9647-
ubsi.source.issued2020de
ubsi.source.issuenumber1de
ubsi.source.linkhttps://www.ubiquitypress.com/de
ubsi.source.pages4de
ubsi.source.placeLondonde
ubsi.source.publisherUbiquity Pressde
ubsi.source.titleJournal of Open Research Softwarede
ubsi.source.volume8de
ubsi.subject.ghbsTKMde
ubsi.subject.ghbsTKWMde
ubsi.subject.ghbsTKFde
ubsi.subject.ghbsTKKCde
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