The JASP guidelines for conducting and reporting a Bayesian analysis
By J. V. van Doorn, D. van den Bergh, Udo Bohm, F. Dablander, Koen Derks, Tim Draws, Alexander Etz, N. Evans, Quentin F. Gronau, J. Haaf and 10 more. Psychonomic Bulletin & Review, 2019
955 citations recorded by the source corpus.
Despite the increasing popularity of Bayesian inference in empirical research, few practical guidelines provide detailed recommendations for how to apply Bayesian procedures and interpret the results. Here we offer specific guidelines for four different stages of Bayesian statistical reasoning in a research setting: planning the analysis, executing the analysis, interpreting the results, and reporting the results. The guidelines for each stage are illustrated with a running example. Although the guidelines are geared towards analyses performed with the open-source statistical software JASP, most guidelines extend to Bayesian inference in general.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/c4bca921d78c0f4fb8569eb9d5c0cb42cbb3ec0b
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- Visualizations with statistical details: The 'ggstatsplot' approach (2021, methodology): “The defaults are designed to follow best practices in both data visualization (Cleveland, 1985; Grant, 2018; Healy, 2018; Tufte, 2001; Wilke, 2019) and (frequentist/Bayesian) statistical reporting (American Psychological Association, 2019; van Doorn et al., 2020).”