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Bayesian inference for psychology. Part II: Example applications with JASP

Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the...

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Detalles Bibliográficos
Autores principales: Wagenmakers, Eric-Jan, Love, Jonathon, Marsman, Maarten, Jamil, Tahira, Ly, Alexander, Verhagen, Josine, Selker, Ravi, Gronau, Quentin F., Dropmann, Damian, Boutin, Bruno, Meerhoff, Frans, Knight, Patrick, Raj, Akash, van Kesteren, Erik-Jan, van Doorn, Johnny, Šmíra, Martin, Epskamp, Sacha, Etz, Alexander, Matzke, Dora, de Jong, Tim, van den Bergh, Don, Sarafoglou, Alexandra, Steingroever, Helen, Derks, Koen, Rouder, Jeffrey N., Morey, Richard D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862926/
https://www.ncbi.nlm.nih.gov/pubmed/28685272
http://dx.doi.org/10.3758/s13423-017-1323-7
Descripción
Sumario:Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely. An important impediment to the widespread adoption of Bayesian tests is arguably the lack of user-friendly software for the run-of-the-mill statistical problems that confront psychologists for the analysis of almost every experiment: the t-test, ANOVA, correlation, regression, and contingency tables. In Part II of this series we introduce JASP (http://www.jasp-stats.org), an open-source, cross-platform, user-friendly graphical software package that allows users to carry out Bayesian hypothesis tests for standard statistical problems. JASP is based in part on the Bayesian analyses implemented in Morey and Rouder’s BayesFactor package for R. Armed with JASP, the practical advantages of Bayesian hypothesis testing are only a mouse click away.