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

By Eric-Jan Wagenmakers, Jonathon Love, Maarten Marsman, Tahira Jamil, Alexander Ly, Josine Verhagen, Ravi Selker, Quentin F. Gronau, Damian Dropmann, Bruno Boutin and 16 more. Psychonomic Bulletin & Review, 2017

1,530 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0a377b127e3bd935f75226fe47a3efa92c4e710b

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Citations in the corpus

Psychological Science Needs a Standard Practice of Reporting the Reliability of Cognitive-Behavioral Measurements (2019, methodology): “A similar argument has been made for the use of Bayesian statistics and sparked the development of JASP, a free open-source software similar to SPSS with the capacity to perform Bayesian analyses in an accessible way (Love et al., 2019; Marsman & Wagenmakers, 2017; Wagenmakers et al., 2018).”
Bayesian alternatives for common null-hypothesis significance tests in psychiatry: a non-technical guide using JASP (2018, methodology): “The recent development of the open-source JASP statistical package [25, 27] provides a straightforward means of performing both classical and Bayesian inference using a graphical interface.”
The JASP guidelines for conducting and reporting a Bayesian analysis (2019, positive): “One may adhere to the adage “only estimate something when there is something to be estimated” (Wagenmakers et al. 2018) and first test whether an effect is present, and then estimate its size (assuming the test provided sufficiently strong evidence against the null), or one may first estimate the…”
Motor Interference, But Not Sensory Interference, Increases Midfrontal Theta Activity and Brain Synchronization during Reactive Control (2021, background): “It has been suggested that BF. 10 represents strong evidence for the alternative hypothesis, while BF, 0.10 indicates strong evidence for the null hypothesis (Jarosz and Wiley, 2014; Van de Schoot et al., 2014; Wagenmakers et al., 2018).”
Concurrent neuroimaging and neurostimulation reveals a causal role for dlPFC in coding of task-relevant information (2020, background): “9 (Team, 2018) to interpret all null effects: BF > 3 indicates evidence for experimental hypothesis, and BF < 1/3 indicates evidence for the null hypothesis (Dienes, 2011; Wagenmakers et al., 2017)).”