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bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework

Makowski, D., Ben-Shachar, M., & Lüdecke, D.

The Journal of Open Source Software, 2019

bayestestR describes what a Bayesian posterior actually implies about an effect: credible intervals, the probability of direction, ROPE-based decisions and Bayes factors, under one vocabulary. It is the easystats package for saying whether an effect exists, how large it is, and whether the size matters.

• DOI: 10.21105/JOSS.01541
• Full text (PDF)

Keywords: Software Development · Bayesian Statistics · Statistical Methods

Cite

Makowski, D., Ben-Shachar, M., & Lüdecke, D. (2019). bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. The Journal of Open Source Software. https://doi.org/10.21105/JOSS.01541

See also

• Indices of Effect Existence and Significance in the Bayesian Framework — Makowski, D., Ben-Shachar, M. S., Chen, S. H. A., & Lüdecke, D. (2019)
• insight: A Unified Interface to Access Information from Model Objects in R — Lüdecke, D., Waggoner, P., & Makowski, D. (2019)
• The psycho Package: an Efficient and Publishing-Oriented Workflow for Psychological Science — Makowski, D. (2018)