The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Detecting Selection Bias in Meta-Analyses with Multiple Outcomes: A Simulation Study
Open accessAbstract
This study explores the performance of classical methods for detecting publication bias—namely, Egger’s regression test, Funnel Plot test, Begg’s Rank Correlation and Trim and Fill method—in meta-analysis of studies that report multiple effects. Publication bias, outcome reporting bias, and a combination of these were generated. Egger’s regression test and the Funnel Plot test were extended to three-level models, and possible cutoffs for the estimator of the Trim and Fill method were explored. Furthermore, we checked whether the combination of results of several methods yielded a better control of Type I error rates. Results show that no method works well across all conditions and that performance depends mainly on the population effect size value and the total variance.
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Methods for testing publication bias in ecological and evolutionary meta‐analyses
Nakagawa, S., Lagisz, M., Jennions, M. D., Koricheva, J., Noble, D. W. A., Parker, T. H., Sánchez‐Tójar, A., Yang, Y., & O'Dea, R. E. (2022) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13724 · Cited by 399
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Metadata
- Authors
- Fernández-Castilla, B., Declercq, L., Jamshidi, L., Beretvas, S. N., Onghena, P., & Van den Noortgate, W.
- Venue
- The Journal of Experimental Education
- Publisher
- Informa UK Limited
- Published
- 2019-04-03
- Volume
- 89
- Issue
- 1
- Pages
- 125-144
- ISSN
- 0022-0973 (ISSN-L)
- 1940-0683
- OpenAlex
- W2932936731
- Cited by
- 285
- References
- 28
- FWCI
- 10.52
- Type
- journal article
- Language
- en
- Open access
- green
- Funders
- Funding was provided through a grant from Fonds Wetenschappelijk Onderzoek
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