ArticleResearch synthesis methods2021
Meta-regression methods to characterize evidence strength using meaningful-effect percentages conditional on study characteristics.
Article in Research synthesis methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 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.
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Who cites it
12 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- The effects of high-intensity interval training on physical fitness and physiological responses in taekwondo athletes: a systematic review and meta-analysis.European journal of applied physiology · 2026Pooled it
- The role of reviewers in the era of systematic reviews and meta-analysis: A practical guide for researchers.Biomolecules & biomedicine · 2025Guideline
- Vascular endothelial growth factor as a potential biomarker in systemic sclerosis: a systematic review and meta-analysis.Frontiers in immunology · 2024Pooled it
- Methods to Address Confounding and Other Biases in Meta-Analyses: Review and Recommendations.Annual review of public health · 2022Pooled it
- The effects of bed rest on cardiometabolic health: A systematic review and meta-analysis.Experimental physiology · 2026Article
- The effectiveness of TEACCH-based interventions in improving adaptive skills in children with autism spectrum disorders: a systematic review and meta-analysis.Translational pediatrics · 2025Article
- Beyond prediction intervals in meta-analysis: reporting the expected proportion of comparable studies with clinically relevant benefit or harm.BMC medical research methodology · 2025Article
- The Optimal Type and Dose of Exercise Interventions on VEGF Levels in Healthy Individuals, as Well as Obesity and Chronic Disease Populations: A Network Meta-Analysis.Biomedicines · 2025Review
- When meta-analysis misleads: the need for methodological integrity in e-cigarette research.Internal and emergency medicine · 2025Article
- The economic rationale for cell-based influenza vaccines in children and adults: A review of cost-effectiveness analyses.Human vaccines & immunotherapeutics · 2024Review
- Evidence for Infant-directed Speech Preference Is Consistent Across Large-scale, Multi-site Replication and Meta-analysis.Open mind : discoveries in cognitive science · 2024Article
- Sensitivity analysis for the interactive effects of internal bias and publication bias in meta-analyses.Research synthesis methods · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Meta-regression analyses usually focus on estimating and testing differences in average effect sizes between individual levels of each meta-regression covariate in turn. These metrics are useful but have limitations: they consider each covariate individually, rather than in combination, and they characterize only the mean of a potentially heterogeneous distribution of effects. We propose additional metrics that address both limitations. Given a chosen threshold representing a meaningfully strong effect size, these metrics address the questions: "For a given joint level of the covariates, what percentage of the population effects are meaningfully strong?" and "For any two joint levels of the covariates, what is the difference between these percentages of meaningfully strong effects?" We provide semiparametric methods for estimation and inference and assess their performance in a simulation study. We apply the proposed methods to meta-regression analyses on memory consolidation and on dietary behavior interventions, illustrating how the methods can provide more information than standard reporting alone. To facilitate implementing the methods in practice, we provide reporting guidelines and simple R code.
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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.