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 ---