Interpretation of tests of heterogeneity and bias in meta‐analysis
Tufts University · University of Ioannina
Abstract
Abstract Statistical tests of heterogeneity and bias, in particular publication bias, are very popular in meta‐analyses. These tests use statistical approaches whose limitations are often not recognized. Moreover, it is often implied with inappropriate confidence that these tests can provide reliable answers to questions that in essence are not of statistical nature. Statistical heterogeneity is only a correlate of clinical and pragmatic heterogeneity and the correlation may sometimes be weak. Similarly, statistical signals may hint to bias, but seen in isolation they cannot fully prove or disprove bias in general, let alone specific causes of bias, such as publication bias in particular. Both false‐positive…
Citation impact
- FWCI
- 14.27
- Percentile
- 100%
- References
- 57
Authors
1Topics & keywords
- Meta-analysis
- Interpretation (philosophy)
- Medicine
- Econometrics
- Statistics
- Psychology
- Computer science
- Economics