Why negative meta-analyses may be false?
Language English Country Netherlands Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
Grant support
103703
Canadian Institutes of Health Research - Canada
106469
Canadian Institutes of Health Research - Canada
PubMed
23402721
DOI
10.1016/j.euroneuro.2013.01.004
PII: S0924-977X(13)00039-4
Knihovny.cz E-resources
- Keywords
- False negative, Meta-analyses, Statistical heterogeneity,
- MeSH
- Biomedical Research methods MeSH
- Genetic Association Studies MeSH
- Humans MeSH
- Evidence-Based Medicine * MeSH
- Meta-Analysis as Topic * MeSH
- Neuroimaging MeSH
- Psychopharmacology methods MeSH
- Reproducibility of Results MeSH
- Models, Statistical * MeSH
- Sample Size MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Results of meta-analyses are regarded as the highest level of evidence. A statistically non-significant effect size from a meta-analysis is typically considered true negative even in the presence of a statistically significant signal in individual studies, presumed to be false positive. Here we provide examples from neuroimaging, genetics and psychopharmacology of why meta-analyses may frequently yield false negative results from true positive findings. This may happen in situations when individual studies report findings in opposing directions, the sum of which yields a non-significant overall effect size. Such non-significant meta-analyses, which show statistical heterogeneity and include studies with opposing effect sizes do not provide an accurate estimate of the overall effect and may have lower heuristic value than individual studies. Over reliance on such meta-analyses may falsely identify certain potentially fruitful research avenues as blind alleys.
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