ArticleBehavior research methods2026
A comparison of multivariate and univariate meta-analysis.
Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multivariate meta-analysis (MVMA) extends univariate meta-analysis (UMA) by jointly synthesizing correlated outcomes across studies, but it requires specification of within-study correlations that may be misspecified in practice. Although prior research suggested that MVMA should outperform UMA when correlations are correctly specified, existing findings have been inconsistent when correlations are misspecified. To clarify these issues, we conducted two simulation studies varying the number of outcomes, the number of studies, per-group sample size, between-study heterogeneity, overall effect sizes, true correlations at both the within- and between-study levels, and the specified within-study correlation, and the proportion of missing data in the second outcome. Results showed that when within-study correlations were correctly specified, UMA outperformed MVMA in more conditions than vice versa, differing from previous conclusions that favored MVMA. When correlations were misspecified, the impact was larger on between-study variance estimates than on overall effect sizes, and UMA again performed better. Finally, when some outcomes had missing data, the estimation and testing for the corresponding outcomes were degraded in both UMA and MVMA.
Indexed as
Identifiers
42321546What OpenQuestion holds
Registered trials
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.