Evidence map›Paper›PMID 23208849›Full record

ArticleStatistics in medicine2013

Estimating within-study covariances in multivariate meta-analysis with multiple outcomes.

Yinghui Wei, Julian P T Higgins

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Statistics in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 17 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 17 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

52 citing papers in PubMed, 17 syntheses or guidelines pooled it.

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  7. Meta-analysis with Robust Variance Estimation: Expanding the Range of Working Models.Prevention science : the official journal of the Society for Prevention Research · 2022
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  10. A meta-analysis of the effect of therapist experience on outcomes for clients with internalizing disorders.Psychotherapy research : journal of the Society for Psychotherapy Research · 2019
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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

2 authors.

Yinghui WeiMRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 0SR, UK. y.wei@ctu.mrc.ac.uk
Julian P T Higgins

Funding

Medical Research Council MC_EX_G0800814Medical Research Council MC_U105285807Medical Research Council U105285807
6 · The paper itself

Abstract

Multivariate meta-analysis allows the joint synthesis of effect estimates based on multiple outcomes from multiple studies, accounting for the potential correlations among them. However, standard methods for multivariate meta-analysis for multiple outcomes are restricted to problems where the within-study correlation is known or where individual participant data are available. This paper proposes an approach to approximating the within-study covariances based on information about likely correlations between underlying outcomes. We developed methods for both continuous and dichotomous data and for combinations of the two types. An application to a meta-analysis of treatments for stroke illustrates the use of the approximated covariance in multivariate meta-analysis with correlated outcomes.

Indexed as

Meta-Analysis as TopicMultivariate AnalysisBiostatisticsCardiovascular AgentsHumansModels, StatisticalOdds RatioRandomized Controlled Trials as TopicStrokeTreatment OutcomeCardiovascular Agents

Identifiers

PMID23208849
PMCPMC3618374

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.