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Bayesian hypothesis testing: Editorial to the Special Issue on Bayesian data analysis

dc.contributor.authorHoijtink, Herbert
dc.contributor.authorChow, Sy-Miin
dc.date.accessioned2017-06-14T16:12:14Z
dc.date.available2017-06-14T16:12:14Z
dc.date.issued2017-06
dc.identifier.urihttps://hdl.handle.net/2027.42/136926
dc.description.abstractIn the past 20 years, there has been a steadily increasing attention and demand for Bayesian data analysis across multiple scientific disciplines, including psychology. Bayesian methods and the related Markov chain Monte Carlo sampling techniques offered renewed ways of handling old and challenging new problems that may be difficult or impossible to handle using classical approaches. Yet, such opportunities and potential improvements have not been sufficiently explored and investigated. This is 1 of 2 special issues in Psychological Methods dedicated to the topic of Bayesian data analysis, with an emphasis on Bayesian hypothesis testing, model comparison, and general guidelines for applications in psychology. In this editorial, we provide an overview of the use of Bayesian methods in psychological research and a brief history of the Bayes factor and the posterior predictive p value. Translational abstracts that summarize the articles in this issue in very clear and understandable terms are included in the Appendix.en_US
dc.language.isoen_USen_US
dc.titleBayesian hypothesis testing: Editorial to the Special Issue on Bayesian data analysisen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPsychology
dc.subject.hlbtoplevelSocial Sciences
dc.contributor.affiliationumPsychology, Department ofen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/136926/1/Bayesian Hypothesis Testing Editorial to the Special Issue on Bayesian.pdf
dc.identifier.doi10.1037/met0000143
dc.identifier.sourcePsychological Methodsen_US
dc.description.filedescriptionDescription of Bayesian Hypothesis Testing Editorial to the Special Issue on Bayesian.pdf : Main Article
dc.owningcollnamePsychology, Department of


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