Spurious Precision in Meta-Analysis
Spurious Precision in Meta-Analysis
| Authors: |
Zuzana Irsova |
|---|---|
| Type: | IES Working Papers |
| Year: | 2023 |
| Number: | 5 |
| Published in: | IES Working Papers 5/2023 |
| Place: | Praha |
| Keywords: | Publication bias, p-hacking, selection models, meta-regression, fun- nel plot, inverse-variance weighting |
| JEL codes: |
C15, C26, C83 |
| Suggested citation: |
Irsova Z., Bom P.R.D., Havranek T., Rachinger H. (2023): " Spurious Precision in Meta-Analysis " IES Working Papers 5/2023. IES FSV. Charles University. |
| Abstract: |
Meta-analysis upweights studies reporting lower standard errors and hence more preci- sion. But in empirical practice, notably in observational research, precision is not given to the researcher. Precision must be estimated, and thus can be p-hacked to achieve statistical significance. Simulations show that a modest dose of spurious precision creates a formidable problem for inverse-variance weighting and bias-correction methods based on the funnel plot. Selection models fail to solve the problem, and the simple mean can beat sophisticated estimators. Cures to publication bias may become worse than the disease. We introduce an approach that surmounts spuriousness: the Meta-Analysis Instrumental Variable Estimator (MAIVE), which employs inverse sample size as an instrument for reported variance. |
| Download: | wp_2023_05_irsova, bom, havranek, rachinger |
