ArticleStatistics in medicine2015
Detecting outlying trials in network meta-analysis.
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 23 papers, 4 of them syntheses that pooled it.
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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
23 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- 8 specific Chinese herbal injections combined with chemotherapy for breast cancer: a systematic review and network meta-analysis of comparative safety and efficacy.Frontiers in pharmacology · 2025Pooled it
- A Bayesian model for combining standardized mean differences and odds ratios in the same meta-analysis.Journal of biopharmaceutical statistics · 2023Pooled it
- Effectiveness of treatments for acute and subacute mechanical non-specific low back pain: a systematic review with network meta-analysis.British journal of sports medicine · 2022Pooled it
- Mapping the characteristics of network meta-analyses on drug therapy: A systematic review.PloS one · 2018Pooled it
- Tipping point analysis in network meta-analysis.Research synthesis methods · 2025Article
- A novel robust meta-analysis model using theResearch synthesis methods · 2025Article
- Sensitivity analysis with iterative outlier detection for systematic reviews and meta-analyses.Statistics in medicine · 2024Article
- Comparative efficacy of mitochondrial agents for bipolar disorder during depressive episodes: a network meta-analysis using frequentist and Bayesian approaches.Psychopharmacology · 2021Review
- Bayesian network meta-regression hierarchical models using heavy-tailed multivariate random effects with covariate-dependent variances.Statistics in medicine · 2021Article
- A variance shrinkage method improves arm-based Bayesian network meta-analysis.Statistical methods in medical research · 2021Article
- The statistical importance of a study for a network meta-analysis estimate.BMC medical research methodology · 2020Article
- Bivariate network meta-analysis for surrogate endpoint evaluation.Statistics in medicine · 2019Article
- Bayesian hierarchical methods for meta-analysis combining randomized-controlled and single-arm studies.Statistical methods in medical research · 2019Article
- Two new approaches for the visualisation of models for network meta-analysis.BMC medical research methodology · 2019Article
- Comparative effectiveness of the different components of care provided in heart failure clinics-protocol for a systematic review and network meta-analysis.Systematic reviews · 2019Article
- Quantifying and presenting overall evidence in network meta-analysis.Statistics in medicine · 2018Article
- Bayesian hierarchical models for network meta-analysis incorporating nonignorable missingness.Statistical methods in medical research · 2017Article
- Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package.Journal of statistical software · 2017Article
- Extending DerSimonian and Laird's methodology to perform network meta-analyses with random inconsistency effects.Statistics in medicine · 2016Article
- Absolute or relative effects? Arm-based synthesis of trial data.Research synthesis methods · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Network meta-analysis (NMA) expands the scope of a conventional pairwise meta-analysis to simultaneously handle multiple treatment comparisons. However, some trials may appear to deviate markedly from the others and thus be inappropriate to be synthesized in the NMA. In addition, the inclusion of these trials in evidence synthesis may lead to bias in estimation. We call such trials trial-level outliers. To the best of our knowledge, while heterogeneity and inconsistency in NMA have been extensively discussed and well addressed, few previous papers have considered the proper detection and handling of trial-level outliers. In this paper, we propose several Bayesian outlier detection measures, which are then applied to a diabetes data set. Simulation studies comparing our approaches in both arm-based and contrast-based model settings are provided in two supporting appendices.
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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.