TY - UNPB
T1 - Examining the reproducibility of meta-analyses in psychology
T2 - A preliminary report
AU - Lakens, Daniel
AU - Page-Gould, Elizabeth
AU - Assen, Marcel A. L. M. van
AU - Spellman, Bobbie
AU - Schönbrodt, Felix D.
AU - Hasselman, Fred
AU - Corker, Katherine S.
AU - Grange, James A.
AU - Sharples, Amanda
AU - Cavender, Corinne
AU - Augusteijn, Hilde Elisabeth Maria
AU - Gerger, Heike
AU - Locher, Cosima
AU - Miller, Ian Dennis
AU - Anvari, Farid
AU - Scheel, Anne M.
N1 - Funding or this research was provided by the Berkeley Initiative for Transparency in the Social Sciences, a program of the Center for Effective Global Action (CEGA), with support from the Laura and John Arnold Foundation
PY - 2017
Y1 - 2017
N2 - Meta-analyses are an important tool to evaluate the literature. It is essential that meta-analyses can easily be reproduced to allow researchers to evaluate the impact of subjective choices on meta-analytic effect sizes, but also to update meta-analyses as new data comes in, or as novel statistical techniques (for example to correct for publication bias) are developed. Research in medicine has revealed meta-analyses often cannot be reproduced. In this project, we examined the reproducibility of meta-analyses in psychology by reproducing twenty published meta-analyses. Reproducing published meta-analyses was surprisingly difficult. 96% of meta-analyses published in 2013-2014 did not adhere to reporting guidelines. A third of these meta-analyses did not contain a table specifying all individual effect sizes. Five of the 20 randomly selected meta-analyses we attempted to reproduce could not be reproduced at all due to lack of access to raw data, no details about the effect sizes extracted from each study, or a lack of information about how effect sizes were coded. In the remaining meta-analyses, differences between the reported and reproduced effect size or sample size were common. We discuss a range of possible improvements, such as more clearly indicating which data were used to calculate an effect size, specifying all individual effect sizes, adding detailed information about equations that are used, and how multiple effect size estimates from the same study are combined, but also sharing raw data retrieved from original authors, or unpublished research reports. This project clearly illustrates there is a lot of room for improvement when it comes to the transparency and reproducibility of published meta-analyses.
AB - Meta-analyses are an important tool to evaluate the literature. It is essential that meta-analyses can easily be reproduced to allow researchers to evaluate the impact of subjective choices on meta-analytic effect sizes, but also to update meta-analyses as new data comes in, or as novel statistical techniques (for example to correct for publication bias) are developed. Research in medicine has revealed meta-analyses often cannot be reproduced. In this project, we examined the reproducibility of meta-analyses in psychology by reproducing twenty published meta-analyses. Reproducing published meta-analyses was surprisingly difficult. 96% of meta-analyses published in 2013-2014 did not adhere to reporting guidelines. A third of these meta-analyses did not contain a table specifying all individual effect sizes. Five of the 20 randomly selected meta-analyses we attempted to reproduce could not be reproduced at all due to lack of access to raw data, no details about the effect sizes extracted from each study, or a lack of information about how effect sizes were coded. In the remaining meta-analyses, differences between the reported and reproduced effect size or sample size were common. We discuss a range of possible improvements, such as more clearly indicating which data were used to calculate an effect size, specifying all individual effect sizes, adding detailed information about equations that are used, and how multiple effect size estimates from the same study are combined, but also sharing raw data retrieved from original authors, or unpublished research reports. This project clearly illustrates there is a lot of room for improvement when it comes to the transparency and reproducibility of published meta-analyses.
UR - https://osf.io/preprints/metaarxiv/xfbjf/
U2 - 10.31222/osf.io/xfbjf
DO - 10.31222/osf.io/xfbjf
M3 - Working paper
BT - Examining the reproducibility of meta-analyses in psychology
PB - MetaArXiv Preprints
ER -