Abstract
Meta-analysis is routinely performed in many scientific disciplines. This analysis is attractive since discoveries are possible even when all the individual studies are underpowered. However, the meta-analytic discoveries may be entirely driven by signal in a single study, and thus nonreplicable. Although the great majority of meta-analyses carried out to date do not infer on the replicability of their findings, it is possible to do so. We provide a selective overview of analyses that can be carried out towards establishing replicability of the scientific findings.We describe methods for the setting where a single outcome is examined in multiple studies (as is common in systematic reviews of medical interventions), as well as for the setting where multiple studies each examine multiple features (as in genomics applications). We also discuss some of the current shortcomings and future directions.
Original language | English |
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Pages (from-to) | 602-620 |
Number of pages | 19 |
Journal | Statistical Science |
Volume | 38 |
Issue number | 4 |
DOIs | |
State | Published - 2023 |
Keywords
- Composite null
- false discovery rate
- meta-analysis
- multiple hypothesis testing
- replicability analysis
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty
- General Mathematics