Evidence map›Paper›PMID 34400814›Full record

ReviewNature human behaviour2021

Bayesian Analysis Reporting Guidelines.

John K Kruschke

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Nature human behaviour, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 197 papers, 15 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
197citing papers in PubMed, 15 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

197 citing papers in PubMed, 15 syntheses or guidelines pooled it.

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  16. Trial
  17. Ticagrelor Compared to Clopidogrel in Acute Coronary Syndromes trial (TC4): a Bayesian pragmatic cluster randomized controlled trial.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2025
    Trial
  18. Patient adherence and response time in electronic patient-reported outcomes: insights from three longitudinal clinical trials.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Trial
  19. Bayesian analysis of the Substrate Ablation vs. Antiarrhythmic Drug Therapy for Symptomatic Ventricular Tachycardia trial.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2023
    Trial
  20. Trial

137 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

John K KruschkeDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, Bloomington, IN, USA. johnkruschke@gmail.com.ORCID http://orcid.org/0000-0003-2001-3485

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Bayes TheoremGuidelines as TopicHumansReproducibility of ResultsResearch Design

Identifiers

PMID34400814
PMCPMC8526359

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.