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Extending Egger's Regression: Detecting Outcome Reporting Bias in Meta-Analysis on Dependent Multiple Outcomes.

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Title: Extending Egger's Regression: Detecting Outcome Reporting Bias in Meta-Analysis on Dependent Multiple Outcomes.
Authors: Park, Sunyoung (AUTHOR), Beretvas, S. Natasha (AUTHOR), Smith, Tyler E. (AUTHOR)
Source: Journal of Experimental Education. 2026, Vol. 94 Issue 4, p1066-1104. 39p.
Subjects: Research bias, Multivariate analysis, Simulation methods & models, Evidence synthesis, Statistical hypothesis testing
Abstract: Outcome reporting bias (ORB) is a form of publication bias resulting from a primary study authors' reporting results for significant outcomes in a meta-analysis (Rothstein et al., 2006). The current study extended Egger's regression test while handling the dependence from multiple effect sizes per study. We compared methods for handling within-study dependence simultaneously (multivariate) versus separately (univariate) and compared the performance of estimation models including RVE, MLMA, and MLMA-RVE. In addition to real data analysis examples, the simulation study explored five characteristics of meta-analytic data in their impact on results. According to the findings, the multivariate model enhances power and the use of RVE or MLMA+RVE with multivariate models worked best. More results, limitations, and directions for future research are discussed. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Experimental Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Extending Egger's Regression: Detecting Outcome Reporting Bias in Meta-Analysis on Dependent Multiple Outcomes.
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  Data: <searchLink fieldCode="AR" term="%22Park%2C+Sunyoung%22">Park, Sunyoung</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Beretvas%2C+S%2E+Natasha%22">Beretvas, S. Natasha</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Smith%2C+Tyler+E%2E%22">Smith, Tyler E.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Experimental+Education%22">Journal of Experimental Education</searchLink>. 2026, Vol. 94 Issue 4, p1066-1104. 39p.
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  Data: <searchLink fieldCode="DE" term="%22Research+bias%22">Research bias</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis%22">Multivariate analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Evidence+synthesis%22">Evidence synthesis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+hypothesis+testing%22">Statistical hypothesis testing</searchLink>
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  Data: Outcome reporting bias (ORB) is a form of publication bias resulting from a primary study authors' reporting results for significant outcomes in a meta-analysis (Rothstein et al., 2006). The current study extended Egger's regression test while handling the dependence from multiple effect sizes per study. We compared methods for handling within-study dependence simultaneously (multivariate) versus separately (univariate) and compared the performance of estimation models including RVE, MLMA, and MLMA-RVE. In addition to real data analysis examples, the simulation study explored five characteristics of meta-analytic data in their impact on results. According to the findings, the multivariate model enhances power and the use of RVE or MLMA+RVE with multivariate models worked best. More results, limitations, and directions for future research are discussed. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Experimental Education is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/00220973.2025.2477720
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      – Code: eng
        Text: English
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        PageCount: 39
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      – SubjectFull: Research bias
        Type: general
      – SubjectFull: Multivariate analysis
        Type: general
      – SubjectFull: Simulation methods & models
        Type: general
      – SubjectFull: Evidence synthesis
        Type: general
      – SubjectFull: Statistical hypothesis testing
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      – TitleFull: Extending Egger's Regression: Detecting Outcome Reporting Bias in Meta-Analysis on Dependent Multiple Outcomes.
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            NameFull: Park, Sunyoung
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              Text: 2026
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