Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Meta-analysis and the science of research synthesis

Abstract

Meta-analysis is the quantitative, scientific synthesis of research results. Since the term and modern approaches to research synthesis were first introduced in the 1970s, meta-analysis has had a revolutionary effect in many scientific fields, helping to establish evidence-based practice and to resolve seemingly contradictory research outcomes. At the same time, its implementation has engendered criticism and controversy, in some cases general and others specific to particular disciplines. Here we take the opportunity provided by the recent fortieth anniversary of meta-analysis to reflect on the accomplishments, limitations, recent advances and directions for future developments in the field of research synthesis.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Various charts and plots common to meta-analysis.

Similar content being viewed by others

References

  1. Jennions, M. D ., Lortie, C. J. & Koricheva, J. in The Handbook of Meta-analysis in Ecology and Evolution (eds Koricheva, J . et al.) Ch. 23, 364–380 (Princeton Univ. Press, 2013)

    Article  Google Scholar 

  2. Roberts, P. D ., Stewart, G. B. & Pullin, A. S. Are review articles a reliable source of evidence to support conservation and environmental management? A comparison with medicine. Biol. Conserv. 132, 409–423 (2006)

    Article  Google Scholar 

  3. Bastian, H ., Glasziou, P . & Chalmers, I. Seventy-five trials and eleven systematic reviews a day: how will we ever keep up? PLoS Med. 7, e1000326 (2010)

    Article  PubMed  PubMed Central  Google Scholar 

  4. Borman, G. D. & Grigg, J. A. in The Handbook of Research Synthesis and Meta-analysis 2nd edn (eds Cooper, H. M . et al.) 497–519 (Russell Sage Foundation, 2009)

  5. Ioannidis, J. P. A. The mass production of redundant, misleading, and conflicted systematic reviews and meta-analyses. Milbank Q. 94, 485–514 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  6. Koricheva, J . & Gurevitch, J. Uses and misuses of meta-analysis in plant ecology. J. Ecol. 102, 828–844 (2014)

    Article  Google Scholar 

  7. Littell, J. H . & Shlonsky, A. Making sense of meta-analysis: a critique of “effectiveness of long-term psychodynamic psychotherapy”. Clin. Soc. Work J. 39, 340–346 (2011)

    Article  Google Scholar 

  8. Morrissey, M. B. Meta-analysis of magnitudes, differences and variation in evolutionary parameters. J. Evol. Biol. 29, 1882–1904 (2016)

    Article  CAS  PubMed  Google Scholar 

  9. Whittaker, R. J. Meta-analyses and mega-mistakes: calling time on meta-analysis of the species richness-productivity relationship. Ecology 91, 2522–2533 (2010)

    Article  PubMed  Google Scholar 

  10. Begley, C. G . & Ellis, L. M. Drug development: Raise standards for preclinical cancer research. Nature 483, 531–533 (2012); clarification 485, 41 (2012)

    Article  CAS  ADS  PubMed  Google Scholar 

  11. Hillebrand, H . & Cardinale, B. J. A critique for meta-analyses and the productivity-diversity relationship. Ecology 91, 2545–2549 (2010)

    Article  PubMed  Google Scholar 

  12. Moher, D . et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6, e1000097 (2009).This paper provides a consensus regarding the reporting requirements for medical meta-analysis and has been highly influential in ensuring good reporting practice and standardizing language in evidence-based medicine, with further guidance for protocols, individual patient data meta-analyses and animal studies.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Moher, D . et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 4, 1 (2015)

    Article  PubMed  PubMed Central  Google Scholar 

  14. Nakagawa, S . & Santos, E. S. A. Methodological issues and advances in biological meta-analysis. Evol. Ecol. 26, 1253–1274 (2012)

    Article  Google Scholar 

  15. Nakagawa, S ., Noble, D. W. A ., Senior, A. M. & Lagisz, M. Meta-evaluation of meta-analysis: ten appraisal questions for biologists. BMC Biol. 15, 18 (2017)

    Article  PubMed  PubMed Central  Google Scholar 

  16. Hedges, L. & Olkin, I. Statistical Methods for Meta-analysis (Academic Press, 1985)

  17. Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 36, 1–48 (2010)

    Article  Google Scholar 

  18. Anzures-Cabrera, J . & Higgins, J. P. T. Graphical displays for meta-analysis: an overview with suggestions for practice. Res. Synth. Methods 1, 66–80 (2010)

    Article  PubMed  Google Scholar 

  19. Egger, M ., Davey Smith, G ., Schneider, M. & Minder, C. Bias in meta-analysis detected by a simple, graphical test. Br. Med. J. 315, 629–634 (1997)

    Article  CAS  Google Scholar 

  20. Duval, S . & Tweedie, R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 56, 455–463 (2000)

    Article  CAS  MATH  PubMed  Google Scholar 

  21. Leimu, R . & Koricheva, J. Cumulative meta-analysis: a new tool for detection of temporal trends and publication bias in ecology. Proc. R. Soc. Lond. B 271, 1961–1966 (2004)

    Article  Google Scholar 

  22. Higgins, J. P. T . & Green, S. (eds) Cochrane Handbook for Systematic Reviews of Interventions: Version 5.1.0 (Wiley, 2011).This large collaborative work provides definitive guidance for the production of systematic reviews in medicine and is of broad interest for methods development outside the medical field.

  23. Lau, J ., Rothstein, H. R . & Stewart, G. B. in The Handbook of Meta-analysis in Ecology and Evolution (eds Koricheva, J . et al.) Ch. 25, 407–419 (Princeton Univ. Press, 2013)

    Article  Google Scholar 

  24. Lortie, C. J ., Stewart, G ., Rothstein, H. & Lau, J. How to critically read ecological meta-analyses. Res. Synth. Methods 6, 124–133 (2015)

    Article  PubMed  Google Scholar 

  25. Murad, M. H . & Montori, V. M. Synthesizing evidence: shifting the focus from individual studies to the body of evidence. J. Am. Med. Assoc. 309, 2217–2218 (2013)

    Article  Google Scholar 

  26. Rasmussen, S. A ., Chu, S. Y ., Kim, S. Y ., Schmid, C. H . & Lau, J. Maternal obesity and risk of neural tube defects: a meta-analysis. Am. J. Obstet. Gynecol. 198, 611–619 (2008)

    Article  PubMed  Google Scholar 

  27. Littell, J. H ., Campbell, M ., Green, S . & Toews, B. Multisystemic therapy for social, emotional, and behavioral problems in youth aged 10–17. Cochrane Database Syst. Rev. https://doi.org/10.1002/14651858.CD004797.pub4 (2005)

  28. Schmidt, F. L. What do data really mean? Research findings, meta-analysis, and cumulative knowledge in psychology. Am. Psychol. 47, 1173–1181 (1992)

    Article  Google Scholar 

  29. Button, K. S . et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat. Rev. Neurosci. 14, 365–376 (2013); erratum 14, 451 (2013)

    Article  CAS  PubMed  Google Scholar 

  30. Parker, T. H . et al. Transparency in ecology and evolution: real problems, real solutions. Trends Ecol. Evol. 31, 711–719 (2016)

    Article  PubMed  Google Scholar 

  31. Stewart, G. Meta-analysis in applied ecology. Biol. Lett. 6, 78–81 (2010)

    Article  PubMed  Google Scholar 

  32. Sutherland, W. J ., Pullin, A. S ., Dolman, P. M . & Knight, T. M. The need for evidence-based conservation. Trends Ecol. Evol. 19, 305–308 (2004)

    Article  PubMed  Google Scholar 

  33. Lowry, E . et al. Biological invasions: a field synopsis, systematic review, and database of the literature. Ecol. Evol. 3, 182–196 (2013)

    Article  PubMed Central  Google Scholar 

  34. Parmesan, C . & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003)

    Article  CAS  ADS  PubMed  Google Scholar 

  35. Jennions, M. D ., Lortie, C. J . & Koricheva, J. in The Handbook of Meta-analysis in Ecology and Evolution (eds Koricheva, J . et al.) Ch. 24, 381–403 (Princeton Univ. Press, 2013)

    Article  Google Scholar 

  36. Balvanera, P . et al. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecol. Lett. 9, 1146–1156 (2006)

    Article  PubMed  Google Scholar 

  37. Cardinale, B. J . et al. Effects of biodiversity on the functioning of trophic groups and ecosystems. Nature 443, 989–992 (2006)

    Article  CAS  ADS  PubMed  Google Scholar 

  38. Rey Benayas, J. M ., Newton, A. C ., Diaz, A. & Bullock, J. M. Enhancement of biodiversity and ecosystem services by ecological restoration: a meta-analysis. Science 325, 1121–1124 (2009)

    Article  ADS  PubMed  CAS  Google Scholar 

  39. Leimu, R ., Mutikainen, P. I. A ., Koricheva, J. & Fischer, M. How general are positive relationships between plant population size, fitness and genetic variation? J. Ecol. 94, 942–952 (2006)

    Article  Google Scholar 

  40. Hillebrand, H. On the generality of the latitudinal diversity gradient. Am. Nat. 163, 192–211 (2004)

    Article  PubMed  Google Scholar 

  41. Gurevitch, J. in The Handbook of Meta-analysis in Ecology and Evolution (eds Koricheva, J . et al.) Ch. 19, 313–320 (Princeton Univ. Press, 2013)

    Article  Google Scholar 

  42. Rustad, L . et al. A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126, 543–562 (2001)

    Article  CAS  ADS  PubMed  Google Scholar 

  43. Adams, D. C. Phylogenetic meta-analysis. Evolution 62, 567–572 (2008)

    Article  PubMed  Google Scholar 

  44. Hadfield, J. D . & Nakagawa, S. General quantitative genetic methods for comparative biology: phylogenies, taxonomies and multi-trait models for continuous and categorical characters. J. Evol. Biol. 23, 494–508 (2010)

    Article  CAS  PubMed  Google Scholar 

  45. Lajeunesse, M. J. Meta-analysis and the comparative phylogenetic method. Am. Nat. 174, 369–381 (2009)

    Article  PubMed  Google Scholar 

  46. Rosenberg, M. S ., Adams, D. C . & Gurevitch, J. MetaWin: Statistical Software for Meta-Analysis with Resampling Tests Version 1 (Sinauer Associates, 1997)

  47. Wallace, B. C . et al. OpenMEE: intuitive, open-source software for meta-analysis in ecology and evolutionary biology. Methods Ecol. Evol. 8, 941–947 (2016)

    Article  Google Scholar 

  48. Gurevitch, J ., Morrison, J. A . & Hedges, L. V. The interaction between competition and predation: a meta-analysis of field experiments. Am. Nat. 155, 435–453 (2000)

    Article  PubMed  Google Scholar 

  49. Adams, D. C ., Gurevitch, J . & Rosenberg, M. S. Resampling tests for meta-analysis of ecological data. Ecology 78, 1277–1283 (1997)

    Article  Google Scholar 

  50. Gurevitch, J . & Hedges, L. V. Statistical issues in ecological meta-analyses. Ecology 80, 1142–1149 (1999)

    Article  Google Scholar 

  51. Schmid, C. H . & Mengersen, K. in The Handbook of Meta-analysis in Ecology and Evolution (eds Koricheva, J . et al.) Ch. 11, 145–173 (Princeton Univ. Press, 2013)

    Article  Google Scholar 

  52. Eysenck, H. J. Exercise in mega-silliness. Am. Psychol. 33, 517 (1978)

    Article  Google Scholar 

  53. Simberloff, D. Rejoinder to: Don’t calculate effect sizes; study ecological effects. Ecol. Lett. 9, 921–922 (2006)

    Article  Google Scholar 

  54. Cadotte, M. W ., Mehrkens, L. R . & Menge, D. N. L. Gauging the impact of meta-analysis on ecology. Evol. Ecol. 26, 1153–1167 (2012)

    Article  Google Scholar 

  55. Koricheva, J ., Jennions, M. D. & Lau, J. in The Handbook of Meta-analysis in Ecology and Evolution (eds Koricheva, J . et al.) Ch. 15, 237–254 (Princeton Univ. Press, 2013)

    Article  Google Scholar 

  56. Lau, J ., Ioannidis, J. P. A ., Terrin, N ., Schmid, C. H . & Olkin, I. The case of the misleading funnel plot. Br. Med. J. 333, 597–600 (2006)

    Article  Google Scholar 

  57. Vetter, D ., Rucker, G. & Storch, I. Meta-analysis: a need for well-defined usage in ecology and conservation biology. Ecosphere 4, 1–24 (2013)

    Article  Google Scholar 

  58. Mengersen, K ., Jennions, M. D. & Schmid, C. H. in The Handbook of Meta-analysis in Ecology and Evolution (eds Koricheva, J. et al.) Ch. 16, 255–283 (Princeton Univ. Press, 2013)

    Article  Google Scholar 

  59. Patsopoulos, N. A ., Analatos, A. A. & Ioannidis, J. P. A. Relative citation impact of various study designs in the health sciences. J. Am. Med. Assoc. 293, 2362–2366 (2005)

    Article  CAS  Google Scholar 

  60. Kueffer, C . et al. Fame, glory and neglect in meta-analyses. Trends Ecol. Evol. 26, 493–494 (2011)

    Article  PubMed  Google Scholar 

  61. Cohnstaedt, L. W. & Poland, J. Review Articles: The black-market of scientific currency. Ann. Entomol. Soc. Am. 110, 90 (2017)

    Article  Google Scholar 

  62. Longo, D. L. & Drazen, J. M. Data sharing. N. Engl. J. Med. 374, 276–277 (2016)

    Article  PubMed  Google Scholar 

  63. Gauch, H. G. Scientific Method in Practice (Cambridge Univ. Press, 2003)

  64. Science Staff. Dealing with data: introduction. Challenges and opportunities. Science 331, 692–693 (2011)

  65. Nosek, B. A . et al. Promoting an open research culture. Science 348, 1422–1425 (2015)

    Article  CAS  ADS  PubMed  PubMed Central  Google Scholar 

  66. Stewart, L. A . et al. Preferred reporting items for a systematic review and meta-analysis of individual participant data: the PRISMA-IPD statement. J. Am. Med. Assoc. 313, 1657–1665 (2015)

    Article  Google Scholar 

  67. Saldanha, I. J . et al. Evaluating Data Abstraction Assistant, a novel software application for data abstraction during systematic reviews: protocol for a randomized controlled trial. Syst. Rev. 5, 196 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  68. Tipton, E. & Pustejovsky, J. E. Small-sample adjustments for tests of moderators and model fit using robust variance estimation in meta-regression. J. Educ. Behav. Stat. 40, 604–634 (2015)

    Article  Google Scholar 

  69. Mengersen, K ., MacNeil, M. A . & Caley, M. J. The potential for meta-analysis to support decision analysis in ecology. Res. Synth. Methods 6, 111–121 (2015)

    Article  PubMed  Google Scholar 

  70. Ashby, D. Bayesian statistics in medicine: a 25 year review. Stat. Med. 25, 3589–3631 (2006)

    Article  MathSciNet  PubMed  Google Scholar 

  71. Senior, A. M . et al. Heterogeneity in ecological and evolutionary meta-analyses: its magnitude and implications. Ecology 97, 3293–3299 (2016)

    Article  PubMed  Google Scholar 

  72. McAuley, L ., Pham, B ., Tugwell, P . & Moher, D. Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses? Lancet 356, 1228–1231 (2000)

    Article  CAS  PubMed  Google Scholar 

  73. Koricheva, J ., Gurevitch, J . & Mengersen, K. (eds) The Handbook of Meta-Analysis in Ecology and Evolution (Princeton Univ. Press, 2013)This book provides the first comprehensive guide to undertaking meta-analyses in ecology and evolution and is also relevant to other fields where heterogeneity is expected, incorporating explicit consideration of the different approaches used in different domains.

  74. Lumley, T. Network meta-analysis for indirect treatment comparisons. Stat. Med. 21, 2313–2324 (2002)

    Article  PubMed  Google Scholar 

  75. Zarin, W . et al. Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review. BMC Med. 15, 3 (2017)

    Article  PubMed  PubMed Central  Google Scholar 

  76. Elliott, J. H . et al. Living systematic reviews: an emerging opportunity to narrow the evidence-practice gap. PLoS Med. 11, e1001603 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  77. Vandvik, P. O ., Brignardello-Petersen, R . & Guyatt, G. H. Living cumulative network meta-analysis to reduce waste in research: a paradigmatic shift for systematic reviews? BMC Med. 14, 59 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  78. Jarvinen, A. A meta-analytic study of the effects of female age on laying date and clutch size in the Great Tit Parus major and the Pied Flycatcher Ficedula hypoleuca. Ibis 133, 62–67 (1991)

    Article  Google Scholar 

  79. Arnqvist, G. & Wooster, D. Meta-analysis: synthesizing research findings in ecology and evolution. Trends Ecol. Evol. 10, 236–240 (1995)

    Article  CAS  PubMed  Google Scholar 

  80. Hedges, L. V ., Gurevitch, J . & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999)

    Article  Google Scholar 

  81. Gurevitch, J ., Curtis, P. S. & Jones, M. H. Meta-analysis in ecology. Adv. Ecol. Res 32, 199–247 (2001)

    Article  CAS  Google Scholar 

  82. Lajeunesse, M. J. phyloMeta: a program for phylogenetic comparative analyses with meta-analysis. Bioinformatics 27, 2603–2604 (2011)

    CAS  PubMed  Google Scholar 

  83. Pearson, K. Report on certain enteric fever inoculation statistics. Br. Med. J. 2, 1243–1246 (1904)

    Article  Google Scholar 

  84. Fisher, R. A. Statistical Methods for Research Workers (Oliver and Boyd, 1925)

  85. Yates, F. & Cochran, W. G. The analysis of groups of experiments. J. Agric. Sci. 28, 556–580 (1938)

    Article  Google Scholar 

  86. Cochran, W. G. The combination of estimates from different experiments. Biometrics 10, 101–129 (1954)

    Article  Google Scholar 

  87. Smith, M. L . & Glass, G. V. Meta-analysis of psychotherapy outcome studies. Am. Psychol. 32, 752–760 (1977)

    Article  CAS  PubMed  Google Scholar 

  88. Glass, G. V. Meta-analysis at middle age: a personal history. Res. Synth. Methods 6, 221–231 (2015)

    Article  PubMed  Google Scholar 

  89. Cooper, H. M ., Hedges, L. V . & Valentine, J. C. (eds) The Handbook of Research Synthesis and Meta-analysis 2nd edn (Russell Sage Foundation, 2009).This book is an important compilation that builds on the ground-breaking first edition to set the standard for best practice in meta-analysis, primarily in the social sciences but with applications to medicine and other fields.

  90. Rosenthal, R. Meta-analytic Procedures for Social Research (Sage, 1991)

  91. Hunter, J. E ., Schmidt, F. L. & Jackson, G. B. Meta-analysis: Cumulating Research Findings Across Studies (Sage, 1982)

  92. Gurevitch, J ., Morrow, L. L ., Wallace, A . & Walsh, J. S. A meta-analysis of competition in field experiments. Am. Nat. 140, 539–572 (1992).This influential early ecological meta-analysis reports multiple experimental outcomes on a longstanding and controversial topic that introduced a wide range of ecologists to research synthesis methods.

    Article  Google Scholar 

  93. O’Rourke, K. An historical perspective on meta-analysis: dealing quantitatively with varying study results. J. R. Soc. Med. 100, 579–582 (2007)

    Article  PubMed  PubMed Central  Google Scholar 

  94. Shadish, W. R . & Lecy, J. D. The meta-analytic big bang. Res. Synth. Methods 6, 246–264 (2015)

    Article  PubMed  Google Scholar 

  95. Glass, G. V. Primary, secondary, and meta-analysis of research. Educ. Res. 5, 3–8 (1976)

    Article  Google Scholar 

  96. DerSimonian, R . & Laird, N. Meta-analysis in clinical trials. Control. Clin. Trials 7, 177–188 (1986)

    Article  CAS  PubMed  Google Scholar 

  97. Lipsey, M. W . & Wilson, D. B. The efficacy of psychological, educational, and behavioral treatment. Confirmation from meta-analysis. Am. Psychol. 48, 1181–1209 (1993)

    Article  CAS  PubMed  Google Scholar 

  98. Chalmers, I. & Altman, D. G. Systematic Reviews (BMJ Publishing Group, 1995)

  99. Moher, D . et al. Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Quality of reporting of meta-analyses. Lancet 354, 1896–1900 (1999)

    Article  CAS  PubMed  Google Scholar 

  100. Higgins, J. P. & Thompson, S. G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21, 1539–1558 (2002)

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We dedicate this Review to the memory of Ingram Olkin and William Shadish, founding members of the Society for Research Synthesis Methodology who made tremendous contributions to the development of meta-analysis and research synthesis and to the supervision of generations of students. We thank L. Lagisz for help in preparing the figures. We are grateful to the Center for Open Science and the Laura and John Arnold Foundation for hosting and funding a workshop, which was the origination of this article. S.N. is supported by Australian Research Council Future Fellowship (FT130100268). J.G. acknowledges funding from the US National Science Foundation (ABI 1262402).

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed equally in designing the study and writing the manuscript, and so are listed alphabetically.

Corresponding authors

Correspondence to Jessica Gurevitch, Julia Koricheva, Shinichi Nakagawa or Gavin Stewart.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks D. Altman, M. Lajeunesse, D. Moher and G. Romero for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gurevitch, J., Koricheva, J., Nakagawa, S. et al. Meta-analysis and the science of research synthesis. Nature 555, 175–182 (2018). https://doi.org/10.1038/nature25753

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature25753

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing