Bayes factor hypothesis testing in meta-analyses: Practical advantages and methodological considerations.
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3/5 보강
OpenAlex 토픽 ·
Meta-analysis and systematic reviews
Statistical Methods in Clinical Trials
Statistical Methods and Bayesian Inference
Bayesian hypothesis testing via Bayes factors offers a principled alternative to classical -value methods in meta-analysis, particularly suited to its cumulative and sequential nature.
- 연구 설계 meta-analysis
APA
Joris Mulder, Robbie C. M. van Aert (2026). Bayes factor hypothesis testing in meta-analyses: Practical advantages and methodological considerations.. Research synthesis methods, 17(3), 589-623. https://doi.org/10.1017/rsm.2025.10060
MLA
Joris Mulder, et al.. "Bayes factor hypothesis testing in meta-analyses: Practical advantages and methodological considerations.." Research synthesis methods, vol. 17, no. 3, 2026, pp. 589-623.
PMID
41992900 ↗
Abstract 한글 요약
Bayesian hypothesis testing via Bayes factors offers a principled alternative to classical -value methods in meta-analysis, particularly suited to its cumulative and sequential nature. Unlike -values, Bayes factors allow for quantifying support both for and against the existence of an effect, facilitate ongoing evidence monitoring, and maintain coherent long-run behavior as additional studies are incorporated. Recent theoretical developments further show how Bayes factors can flexibly control Type I error rates through connections to e-value theory. Despite these advantages, their use remains limited in the meta-analytic literature. This article provides a critical overview of their theoretical properties, methodological considerations-such as prior sensitivity-and practical advantages for evidence synthesis. Two illustrative applications are provided: one on statistical learning in individuals with language impairments, and another on seroma incidence following post-operative exercise in breast cancer patients. New tools supporting these methods are available in the open-source R package BFpack.
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