Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 2020 Apr;4(4):423-434.
doi: 10.1038/s41562-019-0787-z. Epub 2019 Dec 23.

Comparing meta-analyses and preregistered multiple-laboratory replication projects

Affiliations
Comparative Study

Comparing meta-analyses and preregistered multiple-laboratory replication projects

Amanda Kvarven et al. Nat Hum Behav. 2020 Apr.

Erratum in

Abstract

Many researchers rely on meta-analysis to summarize research evidence. However, there is a concern that publication bias and selective reporting may lead to biased meta-analytic effect sizes. We compare the results of meta-analyses to large-scale preregistered replications in psychology carried out at multiple laboratories. The multiple-laboratory replications provide precisely estimated effect sizes that do not suffer from publication bias or selective reporting. We searched the literature and identified 15 meta-analyses on the same topics as multiple-laboratory replications. We find that meta-analytic effect sizes are significantly different from replication effect sizes for 12 out of the 15 meta-replication pairs. These differences are systematic and, on average, meta-analytic effect sizes are almost three times as large as replication effect sizes. We also implement three methods of correcting meta-analysis for bias, but these methods do not substantively improve the meta-analytic results.

PubMed Disclaimer

References

    1. Siddaway, A. P., Wood, A. M. & Hedges, L. V. How to do a systematic review: a best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annu. Rev. Psychol. 70, 747–770 (2019). - PubMed
    1. Cumming, G. The new statistics: why and how. Psychol. Sci. 25, 7–29 (2014). - PubMed
    1. Stanley, T. D. Wheat from chaff: meta-analysis as quantitative literature review. J. Econ. Perspect. 15, 131–150 (2001).
    1. Gurevitch, J., Koricheva, J., Nakagawa, S. & Stewart, G. Meta-analysis and the science of research synthesis. Nature 555, 175–182 (2018). - PubMed
    1. Camerer, C. F. et al. Evaluating replicability of laboratory experiments in economics. Science 351, 1433–1436 (2016). - PubMed

Publication types

LinkOut - more resources