Bias-adjusted meta-analysis using the quality effects model: a Stata tutorial

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), which provides functions for performing a QE meta-analysis.