ArticleResearch synthesis methods2018
Bayesian multivariate meta-analysis of multiple factors.
Article in Research synthesis methods, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 6 of them syntheses that pooled it.
What it found
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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.
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Who cites it
10 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Pooled it
- What proportion of people have long-term pain after total hip or knee replacement? An update of a systematic review and meta-analysis.BMJ open · 2025Pooled it
- Prediction of extubation outcome in critically ill patients: a systematic review and meta-analysis.Critical care (London, England) · 2021Pooled it
- Searching for potential surrogate endpoints of overall survival in clinical trials for patients with prostate cancer.Cancer reports (Hoboken, N.J.) · 2021Pooled it
- Bayesian Methods for Meta-Analyses of Binary Outcomes: Implementations, Examples, and Impact of Priors.International journal of environmental research and public health · 2021Pooled it
- A Bayesian multivariate meta-analysis of prevalence data.Statistics in medicine · 2020Pooled it
- Multivariate meta-analysis with a robustified diagonal likelihood function.Journal of applied statistics · 2025Article
- A Multivariate Meta-Analysis for Optimizing Cell Counts When Using the Mechanical Processing of Lipoaspirate for Regenerative Applications.Pharmaceutics · 2023Article
- The impact of covariance priors on arm-based Bayesian network meta-analyses with binary outcomes.Statistics in medicine · 2020Article
- Borrowing of strength from indirect evidence in 40 network meta-analyses.Journal of clinical epidemiology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
In medical sciences, a disease condition is typically associated with multiple risk and protective factors. Although many studies report results of multiple factors, nearly all meta-analyses separately synthesize the association between each factor and the disease condition of interest. The collected studies usually report different subsets of factors, and the results from separate analyses on multiple factors may not be comparable because each analysis may use different subpopulation. This may impact on selecting most important factors to design a multifactor intervention program. This article proposes a new concept, multivariate meta-analysis of multiple factors (MVMA-MF), to synthesize all available factors simultaneously. By borrowing information across factors, MVMA-MF can improve statistical efficiency and reduce biases compared with separate analyses when factors were missing not at random. As within-study correlations between factors are commonly unavailable from published articles, we use a Bayesian hybrid model to perform MVMA-MF, which effectively accounts for both within- and between-study correlations. The performance of MVMA-MF and the conventional methods are compared using simulations and an application to a pterygium dataset consisting of 29 studies on 8 risk factors.
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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 Socratic graph.