Publication details

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

Authors

WAGENMAKERS Eric-Jan LOVE Jonathon MARSMAN Marteen 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 Sasha ETZ Alexander MATZKE Dora DE JONG Tim VAN DEN BERGH Don SARAFOGLOU Alexandra STEINGROEVER Helen DERKS Koen ROUDER Jeffrey N. MOREY Richard D.

Year of publication 2018
Type Article in Periodical
Magazine / Source Psychonomic Bulletin & Review
MU Faculty or unit

Faculty of Social Studies

Citation
Web https://doi.org/10.3758/s13423-017-1323-7
Doi http://dx.doi.org/10.3758/s13423-017-1323-7
Field Psychology
Keywords Hypothesis test; Statistical evidence; Bayes factor; Posterior distribution
Attached files
Description 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.

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