Supporting materials

Fitting three-level meta-analysis models in R
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Recommended reading

• Viechtbauer W. Conducting meta-analyses in R with the metafor package. Journal of statistical software 2010; 36(3): 1-48.
• Harrer M, Cuijpers P, Furukawa TA, Ebert DD. Doing Meta-Analysis With R: A Hands-On Guide. 1st ed. Boca Raton, FL and London: Chapman & Hall/CRC Press; 2021.
• Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane, 2023. Available from www.training.cochrane.org/handbook.
• Assink, Mark, Carlijn JM Wibbelink, et al. 2016. “Fitting Three-Level Meta-Analytic Models in r: A Step-by-Step Tutorial.” The Quantitative Methods for Psychology 12 (3): 154–74.
• Borenstein, Michael, Julian PT Higgins, Larry V Hedges, and Hannah R Rothstein. 2017. “Basics of Meta-Analysis: I2 Is Not an Absolute Measure of Heterogeneity.” Research Synthesis Methods 8 (1): 5–18.
• Cheung, M. W.-L. (2014). Modeling dependent effect sizes with three-level meta-analyses: a structural equation modeling approach. Psychological methods, 19(2), 211.
• Harrer, M., Cuijpers, P., Furukawa, T. A., & Ebert, D. D. (2021). Doing Meta-Analysis With R: A Hands-On Guide (1st ed.). Boca Raton, FL and London: Chapman & Hall/CRC Press.
• Higgins, J. P., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta‐analysis. Statistics in medicine, 21(11), 1539-1558.
• Higgins, J. P., Thompson, S. G., & Spiegelhalter, D. J. (2009). A re-evaluation of random-effects meta-analysis. Journal of the Royal Statistical Society Series A: Statistics in Society, 172(1), 137-159.
• Team, P. (2023). RStudio: Integrated Development Environment for R. Posit Software, PBC. Boston, MA. Retrieved from http://www.posit.co/
• Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of statistical software, 36(3), 1-48.