A meta-analytic tool that examines the impact of moderator variables on studies' effect size. It is another name for mixed effects model in meta-analysis (moderators are fixed effects, studies are random effects).
From Wikipedia:
Meta-regression examines the impact of moderator variables on study effect size using regression-based techniques. Meta-regression is more effective at this task than are standard meta-analytic techniques. Alternative models include:
- Simple regression does not allow for within study variation.
- Fixed-effects regression does not allow for between study variation. If effect sizes have excess heterogeneity, the fixed effects meta-regression model may be most appropriate.
- Random or mixed effects regression allows for within study variation and between study variation and is therefore the most appropriate model to choose in many applications.
References
- Stanley, T. D., & Doucouliagos, H. (2009). Meta-regression analysis in economics and business. New York: Routledge.
- Stanley, T. D., & Jarrell, S. B. (1989). Meta‐Regression analysis: A quantitative method of literature surveys. Journal of Economic Surveys, 3(2), 161–170.
- Thompson, S. G., & Higgins, J. (2002). How should meta‐regression analyses be undertaken and interpreted? Statistics in medicine, 21(11), 1559–1573. Retrieved from http://rds.epi-ucsf.org/ticr/syllabus/courses/18/2007/05/03/Lecture/readings/Thompson%20-%20Meta-Regression.pdf.
