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Cited by 131

The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.

Sample Sizes and Effect Sizes are Negatively Correlated in Meta-Analyses: Evidence and Implications of a Publication Bias Against NonSignificant Findings

Levine, Timothy R., Asada, Kelli J., Carpenter, Chris·2009·Communication Monographs
DOI 10.1080/03637750903074685
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Abstract

Meta-analysis involves cumulating effects across studies in order to qualitatively summarize existing literatures. A recent finding suggests that the effect sizes reported in meta-analyses may be negatively correlated with study sample sizes. This prediction was tested with a sample of 51 published meta-analyses summarizing the results of 3,602 individual studies. The correlation between effect size and sample size was negative in almost 80 percent of the meta-analyses examined, and the negative correlation was not limited to a particular type of research or substantive area. This result most likely stems from a bias against publishing findings that are not statistically significant. The primary implication is that meta-analyses may systematically overestimate population effect sizes. It is recommended that researchers routinely examine the n–r scatter plot and correlation, or some other indication of publication bias and report this information in meta-analyses.

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Crossref · 10.1080/03637750903074685

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18 of 18 references verified0 citation errors · 0 not checkable

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Citations

Cites

Research works printed but not linked: 69

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Cited by

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Metadata

Authors
Levine, T. R., Asada, K. J., & Carpenter, C.
Venue
Communication Monographs
Publisher
Informa UK Limited
Published
2009-08-11
Volume
76
Issue
3
Pages
286-302
ISSN
  • 0363-7751
  • 1479-5787
DOI
10.1080/03637750903074685
Cited by
131
References
18
Language
en

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.