Bias adjusted meta-analysis using the quality effects model: a Stata tutorial
Date
2026
Authors
Stone, J.C.
Stern, C.
Jia, R.M.
Whitehorn, A.
Ho, H.T.
Doi, S.A.R.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
JBI evidence synthesis, 2026; 24(3):1-17
Statement of Responsibility
Jennifer C. Stone, Cindy Stern, Romy Menghao Jia, Ashley Whitehorn, Hien Thi Ho, Suhail A.R. Doi
Conference Name
Abstract
Meta-analysis is a widely employed method for the synthesis of effect sizes across diverse studies; however, traditional meta-analytic models do not address potential bias due to systematic error. In response, bias-adjusted models of meta-analysis have emerged. One of these is the quality effects (QE) model that was introduced as an approach specifically designed to adjust pooled estimates using information from methodological quality assessments. In this paper, we guide researchers step-by-step through the bias-adjustment process using the QE model in Stata (metan package; StataCorp LLC, Texas USA), which provides functions for performing a QE meta-analysis.
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Dissertation Note
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OnlinePubl
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© 2026 JBI