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A Confidence Interval Robust to Publication Bias for Random-Effects Meta-Analysis of Few Studies

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Title: A Confidence Interval Robust to Publication Bias for Random-Effects Meta-Analysis of Few Studies
Language: English
Authors: Henmi, Masayuki, Hattori, Satoshi (ORCID 0000-0001-5446-2305), Friede, Tim (ORCID 0000-0001-5347-7441)
Source: Research Synthesis Methods. Sep 2021 12(5):674-679.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 6
Publication Date: 2021
Document Type: Journal Articles
Reports - Research
Descriptors: Statistical Analysis, Computation, Bias, Publications, Meta Analysis
DOI: 10.1002/jrsm.1482
ISSN: 1759-2879
Abstract: In meta-analyses including only few studies, the estimation of the between-study heterogeneity is challenging. Furthermore, the assessment of publication bias is difficult as standard methods such as visual inspection or formal hypothesis tests in funnel plots do not provide adequate guidance. Previously, Henmi and Copas (Statistics in Medicine 2010, 29: 2969-2983) proposed a confidence interval for the overall effect in random-effects meta-analysis that is robust to publication bias to some extent. As is evident from their simulations, the confidence intervals have improved coverage compared with standard methods. To our knowledge, the properties of their method have never been assessed for meta-analyses including fewer than five studies. In this manuscript, we propose a variation of the method by Henmi and Copas employing an improved estimator of the between-study heterogeneity, in particular when dealing with few studies only. In a simulation study, the proposed method is compared to several competitors. Overall, we found that our method outperforms the others in terms of coverage probabilities.
Abstractor: As Provided
Entry Date: 2021
Accession Number: EJ1307165
Database: ERIC
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  Data: A Confidence Interval Robust to Publication Bias for Random-Effects Meta-Analysis of Few Studies
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  Data: <searchLink fieldCode="AR" term="%22Henmi%2C+Masayuki%22">Henmi, Masayuki</searchLink><br /><searchLink fieldCode="AR" term="%22Hattori%2C+Satoshi%22">Hattori, Satoshi</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5446-2305">0000-0001-5446-2305</externalLink>)<br /><searchLink fieldCode="AR" term="%22Friede%2C+Tim%22">Friede, Tim</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5347-7441">0000-0001-5347-7441</externalLink>)
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  Data: In meta-analyses including only few studies, the estimation of the between-study heterogeneity is challenging. Furthermore, the assessment of publication bias is difficult as standard methods such as visual inspection or formal hypothesis tests in funnel plots do not provide adequate guidance. Previously, Henmi and Copas (Statistics in Medicine 2010, 29: 2969-2983) proposed a confidence interval for the overall effect in random-effects meta-analysis that is robust to publication bias to some extent. As is evident from their simulations, the confidence intervals have improved coverage compared with standard methods. To our knowledge, the properties of their method have never been assessed for meta-analyses including fewer than five studies. In this manuscript, we propose a variation of the method by Henmi and Copas employing an improved estimator of the between-study heterogeneity, in particular when dealing with few studies only. In a simulation study, the proposed method is compared to several competitors. Overall, we found that our method outperforms the others in terms of coverage probabilities.
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