Meta-analysis and the science of research synthesis

By J. Gurevitch, J. Koricheva, Shinichi Nakagawa, G. Stewart. Nature, 2018

1,449 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Ecological Modeling, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ac5ad1932e31c3ea141366e8e073d6d95869c4ef

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Citations in the corpus

Evidence map of crop diversification strategies at the global scale (2019, background): “In these unweighted analyses, within-and between-study variations are not easily disentangled and heterogeneity may be difficult to analyze properly (Gurevitch et al 2018).”
The effect of characteristics of source credibility on consumer behaviour: A meta-analysis (2020, methodology): “Meta-analysis is a statistical procedure which includes combining data from multiple studies (Dwivedi et al., 2017; Gurevitch et al., 2018; Rana et al., 2015; Zhao et al., 2018).”
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. (2021, background): “Systematic reviews therefore generate various types of knowledge for different users of reviews (such as patients, healthcare providers, researchers, and policy makers) [1 , 2] .”
How effective is nudging? A quantitative review on the effect sizes and limits of empirical nudging studies (2019, background): “This problem of incomplete data reporting is common in many primary publications (Gurevitch et al., 2018).”
A global meta-analyses of the response of multi-taxa diversity to grazing intensity in grasslands (2019, methodology): “We followed the methods of Hedges et al (1999) and Gurevitch et al (2018) to evaluate the effects of grazing on the diversity indices of plants, arthropods, and microbes.”
Soil erosion modelling: A global review and statistical analysis (2020, neutral): “A meta-regression analysis sensu stricto (Gurevitch et al., 2018) of the GASEMT data was not part of our analysis scope as the aforementioned heterogeneity of the database and the lack of georeferenced information about the study areas precluded this option.”
Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension (2021, methodology): “The conclusions drawn from systematic reviews and metaanalyses are only as strong as the studies that comprise them (Gurevitch et al., 2018).”