TY - JOUR
T1 - Bayesian inference for psychology. Part II
T2 - Example applications with JASP
AU - Wagenmakers, Eric-Jan
AU - Love, Jonathon
AU - Marsman, Maarten
AU - Jamil, Tahira
AU - Ly, Alexander
AU - Verhagen, Josine
AU - Selker, Ravi
AU - Gronau, Quentin F.
AU - Dropmann, Damian
AU - Boutin, Bruno
AU - Meerhoff, Frans
AU - Knight, Patrick
AU - Raj, Akash
AU - van Kesteren, Erik-Jan
AU - van Doorn, Johnny
AU - Smira, Martin
AU - Epskamp, Sacha
AU - Etz, Alexander
AU - Matzke, Dora
AU - de Jong, Tim
AU - van den Bergh, Don
AU - Sarafoglou, Alexandra
AU - Steingroever, Helen
AU - Derks, Koen
AU - Rouder, Jeffrey N.
AU - Morey, Richard D.
PY - 2018/2
Y1 - 2018/2
N2 - 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.
AB - 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.
KW - Bayes factor
KW - Hypothesis test
KW - Posterior distribution
KW - Statistical evidence
U2 - 10.3758/s13423-017-1323-7
DO - 10.3758/s13423-017-1323-7
M3 - Article
C2 - 28779455
SN - 1069-9384
VL - 25
SP - 58
EP - 76
JO - Psychonomic bulletin & review
JF - Psychonomic bulletin & review
IS - 1
ER -