SynthesisStatistics in medicine2013
Multivariate meta-analysis of mixed outcomes: a Bayesian approach.
Synthesis 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 39 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Acetabular dysplasia and the risk of developing hip osteoarthritis within 4-8 years: An individual participant data meta-analysis of 18,807 hips from the World COACH consortium.Osteoarthritis and cartilage · 2025Pooled it
- Handling missing within-study correlations in the evaluation of surrogate endpoints.Statistics in medicine · 2023Pooled it
- A Bayesian multivariate meta-analysis of prevalence data.Statistics in medicine · 2020Pooled it
- Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences.Statistical methods in medical research · 2018Pooled it
- The impact of pharmaceutical care interventions for medication underuse in older people: a systematic review and meta-analysis.British journal of clinical pharmacology · 2015Pooled it
- Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement.Statistics in medicine · 2015Pooled it
- Review
- Article
- Bayesian Network Meta-Analysis With One or Two Continuous Outcomes Measured at Multiple Time Points Using Gaussian Random Walks With Drift.Statistics in medicine · 2026Article
- Change ofFrontiers in psychology · 2026Article
- A New Frequentist Implementation of the Daniels and Hughes Bivariate Meta-Analysis Model for Surrogate Endpoint Evaluation.Biometrical journal. Biometrische Zeitschrift · 2025Article
- Article
- Using Bayesian Evidence Synthesis Methods to Incorporate Real-World Evidence in Surrogate Endpoint Evaluation.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Article
- A Bayesian Mixture Modelling of Stop Signal Reaction Time Distributions: The Second Contextual Solution for the Problem of Aftereffects of Inhibition on SSRT Estimations.Brain sciences · 2021Article
- Classifying information-sharing methods.BMC medical research methodology · 2021Article
- Combining Correlated Outcomes and Surrogate Endpoints in a Network Meta-Analysis of Colorectal Cancer Treatments.Cancers · 2020Article
- Random-effects meta-analysis of combined outcomes based on reconstructions of individual patient data.Research synthesis methods · 2020Article
- Uptake of methodological advances for synthesis of continuous and time-to-event outcomes would maximize use of the evidence base.Journal of clinical epidemiology · 2020Review
- Multivariate network meta-analysis incorporating class effects.BMC medical research methodology · 2020Article
- Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Multivariate random effects meta-analysis (MRMA) is an appropriate way for synthesizing data from studies reporting multiple correlated outcomes. In a Bayesian framework, it has great potential for integrating evidence from a variety of sources. In this paper, we propose a Bayesian model for MRMA of mixed outcomes, which extends previously developed bivariate models to the trivariate case and also allows for combination of multiple outcomes that are both continuous and binary. We have constructed informative prior distributions for the correlations by using external evidence. Prior distributions for the within-study correlations were constructed by employing external individual patent data and using a double bootstrap method to obtain the correlations between mixed outcomes. The between-study model of MRMA was parameterized in the form of a product of a series of univariate conditional normal distributions. This allowed us to place explicit prior distributions on the between-study correlations, which were constructed using external summary data. Traditionally, independent 'vague' prior distributions are placed on all parameters of the model. In contrast to this approach, we constructed prior distributions for the between-study model parameters in a way that takes into account the inter-relationship between them. This is a flexible method that can be extended to incorporate mixed outcomes other than continuous and binary and beyond the trivariate case. We have applied this model to a motivating example in rheumatoid arthritis with the aim of incorporating all available evidence in the synthesis and potentially reducing uncertainty around the estimate of interest.
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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 OpenQuestion graph.