Methods focused on contrasting and combining results from different studies, in the hope of increasing precision and external validity.

Meta-analysis refers to methods focused on contrasting and combining results from different studies, in the hope of identifying patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies.

Some aspects of research that can be meta-analyzed include (credit due to this answer):

  • Heterogeneity of results
    • Moderators (see also )
      • Construct measurement and analytic methods
        • Study quality
      • Population
    • Publication bias
      • Fail safe N – number of null results necessary to reduce an effect size to insignificance

References (credit due to this question: Looking for good introductory treatment of meta-analysis)

- Anglim, J. (2009, December 7). Meta-analysis: Tips, resources, and software. Jeromy Anglim's Blog: Psychology and Statistics. Retrieved from
- Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2011). Introduction to meta-analysis. John Wiley & Sons. Sample chapters available at
- Dallal, G. E. (2003). Meta analysis. Retrieved from
- DeCoster, J. (2004). Meta-analysis notes. Retrieved February 22, 2014 from
- Egger, M., Smith, G. D., & Altman, D. (Eds.). (2008). Systematic reviews in health care: meta-analysis in context. John Wiley & Sons.
- Harrison, F. (2011). Getting started with meta‐analysis. Methods in Ecology and Evolution, 2(1), 1–10.
- Persuad, R., & Evans, S. (1996). Misleading meta-analysis: "Fail safe N" is a useful mathematical measure of the stability of results. British Medical Journal, 312, 125. Retrieved from
- Wolf, F. M. (1986). Meta-analysis: Quantitative methods for research synthesis (Vol. 59). Sage.