ArticleStatistics in medicine2016
Extending DerSimonian and Laird's methodology to perform network meta-analyses with random inconsistency effects.
Article in Statistics in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 5 of them syntheses that pooled 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.
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
23 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Burden and Challenges of Managing Hypertension in People Living with Human Immunodeficiency Virus (HIV) Infection in Sub-Saharan Africa: A Mixed Systematic Review and Meta-Analysis.International journal of public health · 2025Pooled it
- Impacts of digital social media detox for mental health: A systematic review and meta-analysis.Narra J · 2024Pooled it
- Programmed Death 1 and Programmed Death Ligand 1 Inhibitors in Advanced and Recurrent Urothelial Carcinoma: Meta-analysis of Single-Agent Studies.Clinical genitourinary cancer · 2020Pooled it
- Comparison of Cardiovascular Events Among Users of Different Classes of Antihypertension Medications: A Systematic Review and Network Meta-analysis.JAMA network open · 2020Pooled it
- Efficacy and safety of anticholinergics for children or adolescents with idiopathic overactive bladder: systematic review and meta-analysis.International urology and nephrology · 2019Pooled it
- Immunomodulatory therapies in community-acquired pneumonia: a protocol for a systematic review and network meta-analysis.BMJ open · 2025Article
- Network meta-analysis made simple: A composite likelihood approach.Research synthesis methods · 2025Article
- Review
- A simulation study to compare different estimation approaches for network meta-analysis and corresponding methods to evaluate the consistency assumption.BMC medical research methodology · 2020Article
- Identifying inconsistency in network meta-analysis: Is the net heat plot a reliable method?Statistics in medicine · 2019Article
- Two new approaches for the visualisation of models for network meta-analysis.BMC medical research methodology · 2019Article
- Hypothesis testing in Bayesian network meta-analysis.BMC medical research methodology · 2018Article
- Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.Statistical methods in medical research · 2018Article
- A framework for identifying treatment-covariate interactions in individual participant data network meta-analysis.Research synthesis methods · 2018Article
- A matrix-based method of moments for fitting multivariate network meta-analysis models with multiple outcomes and random inconsistency effects.Biometrics · 2018Article
- A design-by-treatment interaction model for network meta-analysis and meta-regression with integrated nested Laplace approximations.Research synthesis methods · 2018Article
- A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio.Statistics in medicine · 2018Article
- Paule-Mandel estimators for network meta-analysis with random inconsistency effects.Research synthesis methods · 2017Article
- Multivariate and network meta-analysis of multiple outcomes and multiple treatments: rationale, concepts, and examples.BMJ (Clinical research ed.) · 2017Article
- Two new methods to fit models for network meta-analysis with random inconsistency effects.BMC medical research methodology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Network meta-analysis is becoming more popular as a way to compare multiple treatments simultaneously. Here, we develop a new estimation method for fitting models for network meta-analysis with random inconsistency effects. This method is an extension of the procedure originally proposed by DerSimonian and Laird. Our methodology allows for inconsistency within the network. The proposed procedure is semi-parametric, non-iterative, fast and highly accessible to applied researchers. The methodology is found to perform satisfactorily in a simulation study provided that the sample size is large enough and the extent of the inconsistency is not very severe. We apply our approach to two real examples.
Indexed as
Identifiers
What 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.