ArticleResearch synthesis methods2017
Paule-Mandel estimators for network meta-analysis with random inconsistency effects.
Article in Research synthesis methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 6 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
18 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- The severity of dissociation and dissociative phenomena in non-affective psychosis: a systematic review and meta-analyses.BMC psychiatry · 2026Pooled it
- Sex-related differences in end-of-life decision-making in patients with traumatic brain injury: a systematic review and meta-analysis.BMC palliative care · 2026Pooled it
- High intake of ultra-processed food is associated with dementia in adults: a systematic review and meta-analysis of observational studies.Journal of neurology · 2024Pooled it
- Ultra-Processed Food Intake Is Associated with Non-Alcoholic Fatty Liver Disease in Adults: A Systematic Review and Meta-Analysis.Nutrients · 2023Pooled it
- A Meta-Analysis of Autism and Clinical High-Risk for Psychosis is Too Premature. Comment on: Vaquerizo-Serrano, Salazar de Pablo, Singh & Santosh (2021).Journal of autism and developmental disorders · 2022Pooled it
- Systematic review and network meta-analysis assess the comparative efficacy and safety of transsphenoidal surgery for pituitary tumor.Neurosurgical review · 2021Pooled it
- Article
- Impact of Atrial Fibrillation on the Outcome of Patients with Brugada Syndrome: A Meta-Analysis.Journal of cardiovascular development and disease · 2025Review
- Methodological review of NMA bias concepts provides groundwork for the development of a list of concepts for potential inclusion in a new risk of bias tool for network meta-analysis (RoB NMA Tool).Systematic reviews · 2024Article
- Association between sex and survival after out-of-hospital cardiac arrest: A systematic review and meta-analysis.Journal of the American College of Emergency Physicians open · 2023Article
- A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis.Systematic reviews · 2021Article
- 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
- Multistep estimators of the between-study variance: The relationship with the Paule-Mandel estimator.Statistics in medicine · 2018Article
- A design-by-treatment interaction model for network meta-analysis and meta-regression with integrated nested Laplace approximations.Research synthesis methods · 2018Article
- Paule-Mandel estimators for network meta-analysis with random inconsistency effects.Research synthesis methods · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Network meta-analysis is used to simultaneously compare multiple treatments in a single analysis. However, network meta-analyses may exhibit inconsistency, where direct and different forms of indirect evidence are not in agreement with each other, even after allowing for between-study heterogeneity. Models for network meta-analysis with random inconsistency effects have the dual aim of allowing for inconsistencies and estimating average treatment effects across the whole network. To date, two classical estimation methods for fitting this type of model have been developed: a method of moments that extends DerSimonian and Laird's univariate method and maximum likelihood estimation. However, the Paule and Mandel estimator is another recommended classical estimation method for univariate meta-analysis. In this paper, we extend the Paule and Mandel method so that it can be used to fit models for network meta-analysis with random inconsistency effects. We apply all three estimation methods to a variety of examples that have been used previously and we also examine a challenging new dataset that is highly heterogenous. We perform a simulation study based on this new example. We find that the proposed Paule and Mandel method performs satisfactorily and generally better than the previously proposed method of moments because it provides more accurate inferences. Furthermore, the Paule and Mandel method possesses some advantages over likelihood-based methods because it is both semiparametric and requires no convergence diagnostics. Although restricted maximum likelihood estimation remains the gold standard, the proposed methodology is a fully viable alternative to this and other estimation methods.
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.