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Bayesian Analysis Reporting Guidelines

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  • John K. Kruschke

    (Indiana University, Bloomington)

Abstract

Previous surveys of the literature have shown that reports of statistical analyses often lack important information, causing lack of transparency and failure of reproducibility. Editors and authors agree that guidelines for reporting should be encouraged. This Review presents a set of Bayesian analysis reporting guidelines (BARG). The BARG encompass the features of previous guidelines, while including many additional details for contemporary Bayesian analyses, with explanations. An extensive example of applying the BARG is presented. The BARG should be useful to researchers, authors, reviewers, editors, educators and students. Utilization, endorsement and promotion of the BARG may improve the quality, transparency and reproducibility of Bayesian analyses.

Suggested Citation

  • John K. Kruschke, 2021. "Bayesian Analysis Reporting Guidelines," Nature Human Behaviour, Nature, vol. 5(10), pages 1282-1291, October.
    • Handle: RePEc:nat:nathum:v:5:y:2021:i:10:d:10.1038_s41562-021-01177-7
    DOI: 10.1038/s41562-021-01177-7
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    References listed on IDEAS

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    Cited by:

    1. Manh-Toan Ho & Thanh-Huyen T. Nguyen & Minh-Hoang Nguyen & Viet-Phuong La & Quan-Hoang Vuong, 2022. "Virtual tree, real impact: how simulated worlds associate with the perception of limited resources," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    2. Yasuhiro Kanakogi & Michiko Miyazaki & Hideyuki Takahashi & Hiroki Yamamoto & Tessei Kobayashi & Kazuo Hiraki, 2022. "Third-party punishment by preverbal infants," Nature Human Behaviour, Nature, vol. 6(9), pages 1234-1242, September.

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