meta-analysis

Meta-Analysis Best Practice

When comparing results across studies or experiments:

1. Report effect sizes, not just p-values
2. Use standardized metrics for cross-study comparison
3. Account for heterogeneity (different setups, datasets, seeds)
4. Report confidence intervals alongside point estimates
5. Use forest plots to visualize cross-study comparisons
6. Identify and discuss outliers or inconsistent results
7. Consider publication bias when interpreting aggregate results