Meta-analysis and the science of research synthesis

• Published in: Nature (London) Vol. 555; no. 7695; pp. 175 - 182
• Main Authors: Gurevitch, Jessica, Koricheva, Julia, Nakagawa, Shinichi, Stewart, Gavin
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 08.03.2018; Nature Publishing Group
• Subjects: 631/158/670; 692/308/409; Ecology; Humanities and Social Sciences; Meta-analysis; Methods; multidisciplinary; review-article; Science; Scientific communication; Studies; Synthesis; Systematic review
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/nature25753

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. Meta-analysis—the quantitative, scientific synthesis of research results—has been both revolutionary and controversial, with rapid advances and broad implementation resulting in substantial scientific advances, but not without pitfalls. The rise of research synthesis Four decades after its introduction, meta-analysis has become a widely accepted research synthesis tool. In this Review, Jessica Gurevitch and colleagues explore the history, development and current state of meta-analytic practice in the biological sciences. They outline the contributions that it has made to several disciplines, particularly ecology, evolutionary biology and conservation, where the number of meta-analyses has increased exponentially over time. They discuss some of the pitfalls of these types of analyses and summarize recent developments such as the use of machine learning and artificial intelligence. They suggest that evidence synthesis should become a regular companion to primary scientific research to maximize the effectiveness of scientific inquiry, but call for the rigorous application of stricter quality criteria for the publication of meta-analyses.