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Indices of Effect Existence and Significance in the Bayesian Framework

Makowski, D., Ben-Shachar, M. S., Chen, S. H. A., & Lüdecke, D.

Frontiers in Psychology, 2019

There are several ways to say a Bayesian effect "exists" — the probability of direction, ROPE coverage, Bayes factors, MAP-based p-values — and they do not always agree. This paper compares them on simulated data, sets out which to report, and maps each onto the frequentist p-value researchers are arriving from.

• DOI: 10.3389/fpsyg.2019.02767
• Full text (PDF)

Keywords: Bayesian Statistics · Statistical Methods

Cite

Makowski, D., Ben-Shachar, M. S., Chen, S. H. A., & Lüdecke, D. (2019). Indices of Effect Existence and Significance in the Bayesian Framework. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2019.02767

See also

• bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework — Makowski, D., Ben-Shachar, M., & Lüdecke, D. (2019)
• Choosing informative priors in Bayesian regression models: a simulation study and tutorial using Stan and R. — Lüdecke, D., Makowski, A. C., Klein, J., Ben-Shachar, M. S., & Makowski, D. (2026)
• insight: A Unified Interface to Access Information from Model Objects in R — Lüdecke, D., Waggoner, P., & Makowski, D. (2019)