Reverse-Bayes Methods for Evidence Assessment and Research Synthesis

Autor/inn/en	Held, Leonhard; Matthews, Robert; Ott, Manuela; Pawel, Samuel
Titel	Reverse-Bayes Methods for Evidence Assessment and Research Synthesis
Quelle	In: Research Synthesis Methods, 13 (2022) 3, S.295-314 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Held, Leonhard) ORCID (Matthews, Robert) ORCID (Ott, Manuela) ORCID (Pawel, Samuel)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1759-2879
DOI	10.1002/jrsm.1538
Schlagwörter	Bayesian Statistics; Statistical Inference; Hypothesis Testing; Credibility; Scientific Research; Probability; Replication (Evaluation); Risk; Data Interpretation; Meta Analysis; Randomized Controlled Trials; Drug Therapy; Death; Patients + Suchen Sie Ihr Suchwort? Inferential statistics; Schließende Statistik; Hypothesenprüfung; Hypothesentest; Glaubwürdigkeit; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Risiko; Data evaluation; Datenauswertung; Meta-analysis; Metaanalyse; Sterbefall; Tod; Todesfall; Patient
Abstract	It is now widely accepted that the standard inferential toolkit used by the scientific research community--null-hypothesis significance testing (NHST)--is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects long-standing issues concerning Bayesian methods, the principal alternative to NHST. We report on recent work that builds on an approach to inference put forward over 70 years ago to address the well-known "Problem of Priors" in Bayesian analysis, by reversing the conventional prior-likelihood-posterior ("forward") use of Bayes' theorem. Such Reverse-Bayes analysis allows priors to be deduced from the likelihood by requiring that the posterior achieve a specified level of credibility. We summarise the technical underpinning of this approach, and show how it opens up new approaches to common inferential challenges, such as assessing the credibility of scientific findings, setting them in appropriate context, estimating the probability of successful replications, and extracting more insight from NHST while reducing the risk of misinterpretation. We argue that Reverse-Bayes methods have a key role to play in making Bayesian methods more accessible and attractive for evidence assessment and research synthesis. As a running example we consider a recently published meta-analysis from several randomised controlled trials (RCTs) investigating the association between corticosteroids and mortality in hospitalised patients with COVID-19. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01