Evidence map›Paper›PMID 41626939›Full record

ArticleResearch synthesis methods2025

A novel robust meta-analysis model using the

Yue Wang, Jianhua Zhao, Fen Jiang, Lei Shi, Jianxin Pan

Abstract read
In one paragraph

Article in Research synthesis methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yue WangSchool of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China.
Jianhua ZhaoSchool of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China.ORCID https://orcid.org/0000-0003-4028-8478
Fen JiangSchool of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China.
Lei ShiSchool of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China.
Jianxin PanGuangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College, Zhuhai, China.

Funding

National Natural Science Foundation of China 11931015National Natural Science Foundation of China 12161089National Natural Science Foundation of China 12271047National Natural Science Foundation of China 12271471National Office for Philosophy and Social Sciences 22VRCO49National Office for Philosophy and Social Sciences 22&ZD158
6 · The paper itself

Abstract

Random effects meta-analysis model is an important tool for integrating results from multiple independent studies. However, the standard model is based on the assumption of normal distributions for both random effects and within-study errors, making it susceptible to outlying studies. Although robust modeling using the

Indexed as

Meta-Analysis as TopicModels, StatisticalAlgorithmsComputer SimulationData Interpretation, StatisticalHumansLikelihood FunctionsReproducibility of ResultsResearch Designexpectation maximizationmeta-analysisoutlier accommodationoutlier detectionrobustness

Identifiers

PMID41626939
PMCPMC12527545

What OpenQuestion holds

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Registered trials

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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.