bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework
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Makowski et al., (2019). bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework. Journal of Open Source Software, 4(40), 1541, https://doi.org/10.21105/joss.01541
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For percentage in ROPE interpretation, suggested reference values are: >99% negligible, >97.5% probably negligible, ≤97.5 and ≥2.5% undecided, <2.5% probably significant, <1% significant.
“For percentage in ROPE interpretation, the following reference values have been suggested:>99% = negligible>97.5% = probably negligible≤97.5 and ≥2.5% = undecided<2.5% = probably significant<1% = significant”
From Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders (2022) · cites this paper as [302]
The ROPE and Test for Practical Equivalence section (page not provided) describes interpreting the proportion of an HDI inside the ROPE and gives rules for complete inclusion, complete exclusion, and undecided cases. It does not suggest the claimed 99%, 97.5%, 2.5%, or 1% reference values or their verbal labels. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe percentage in region of practical equivalence (ROPE) indexes the magnitude of an effect where the ROPE is the range of effect size values considered to be practically equivalent to the null.
“The percentage in ROPE indexes the magnitude of an effect where the ROPE is the range of effect size values considered to be practically equivalent to the null [302, 305].”
From Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders (2022) · cites this paper as [302]
The “ROPE and Test for Practical Equivalence” section defines the ROPE as a range around the null containing values equivalent to it for practical purposes, and says the reported proportion is the share of the posterior HDI within that range. It describes that proportion as a criterion for practical-equivalence testing, not as an index of effect magnitude. No page number is available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThe probability of direction (pd) is an index of the existence of an effect and is represented by the certainty (50-100%) in the direction, positive or negative.
“The pd is an index of the existence of an effect and is represented by the certainty (50-100%) in the direction, positive or negative [302, 305].”
For pd interpretation, suggested reference values are: ≤95% uncertain, >95% possibly existing, >97% likely existing, >99% probably existing, >99.9% certainly existing.
“For pd interpretation, the following reference values have been suggested:≤95% = uncertain>95% = possibly existing>97% = likely existing>99% = probably existing>99.9% = certainly existing”
From Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders (2022) · cites this paper as [302]
The “Probability of Direction (pd)” section defines pd and gives a 98% example, but it does not give the claimed interpretation thresholds or labels. Searches for the labels and the 95%, 97%, 99%, and 99.9% cutoffs found no such guidance in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
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“• The percentage in ROPE indexes the magnitude of an effect where the ROPE is the range of effect size values considered to be practically equivalent to the null [302, 305].”
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Influential
- Authors
- Makowski, D., Ben-Shachar, M., & Lüdecke, D.
- Affiliations
- Nanyang Technological University (SG)
- University Medical Center Hamburg-Eppendorf (DE)
- Venue
- Journal of Open Source Software
- Publisher
- The Open Journal
- Published
- 2019-08-13
- Volume
- 4
- Issue
- 40
- Pages
- 1541
- ISSN
- 2475-9066 (ISSN-L)
- OpenAlex
- W2968619018
- Cited by
- 1,483
- References
- 16
- Citations by year
- 2026: 243 · 2025: 302 · 2024: 249 · 2023: 250 · 2022: 209 · 2021: 154 · 2020: 66 · 2019: 7 · 2018: 1 · 2012: 1
- FWCI
- 85.06
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- The Journal of Open Source Software (publishedVersion, cc-by)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Computer Science › Artificial Intelligence › Data Analysis with R
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Keywords
- Bayesian analysis, effect size estimation, uncertainty quantification, significance testing, R package, posterior distribution
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