Evidence map›Paper›PMID 25475839›Full record

ArticleStatistics in medicine2015

Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis.

Rebecca M Turner, Dan Jackson, Yinghui Wei, Simon G Thompson, Julian P T Higgins

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Statistics in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 172 papers, 83 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
172citing papers in PubMed, 83 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

172 citing papers in PubMed, 83 syntheses or guidelines pooled it.

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  9. Treatments for renal cell carcinoma: NICE Pilot Treatment Pathways Appraisal.Health technology assessment (Winchester, England) · 2026
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  19. Systematic review and indirect treatment comparisons of ritlecitinib against baricitinib in alopecia areata.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025
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112 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

5 authors.

Rebecca M TurnerMRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, U.K.
Dan Jackson
Yinghui Wei
Simon G Thompson
Julian P T Higgins

Funding

British Heart Foundation RG/08/014/24067Medical Research Council MC_U105260558Medical Research Council MR/K025643/1Medical Research Council MR/L003120/1Medical Research Council U105260558
6 · The paper itself

Abstract

Numerous meta-analyses in healthcare research combine results from only a small number of studies, for which the variance representing between-study heterogeneity is estimated imprecisely. A Bayesian approach to estimation allows external evidence on the expected magnitude of heterogeneity to be incorporated. The aim of this paper is to provide tools that improve the accessibility of Bayesian meta-analysis. We present two methods for implementing Bayesian meta-analysis, using numerical integration and importance sampling techniques. Based on 14,886 binary outcome meta-analyses in the Cochrane Database of Systematic Reviews, we derive a novel set of predictive distributions for the degree of heterogeneity expected in 80 settings depending on the outcomes assessed and comparisons made. These can be used as prior distributions for heterogeneity in future meta-analyses. The two methods are implemented in R, for which code is provided. Both methods produce equivalent results to standard but more complex Markov chain Monte Carlo approaches. The priors are derived as log-normal distributions for the between-study variance, applicable to meta-analyses of binary outcomes on the log odds-ratio scale. The methods are applied to two example meta-analyses, incorporating the relevant predictive distributions as prior distributions for between-study heterogeneity. We have provided resources to facilitate Bayesian meta-analysis, in a form accessible to applied researchers, which allow relevant prior information on the degree of heterogeneity to be incorporated.

Indexed as

Bayes TheoremMeta-Analysis as TopicDatabases, BibliographicData Interpretation, StatisticalHumansLogistic ModelsReview Literature as TopicBayesian methodsheterogeneitymeta-analysisprior distributions

Identifiers

PMID25475839
PMCPMC4383649

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.