meta-analysis
Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.
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tessl review fix ./researchclaw/skills/builtin/experiment/meta-analysis/SKILL.mdMeta-Analysis Best Practice
When comparing results across studies or experiments:
- Report effect sizes, not just p-values
- Use standardized metrics for cross-study comparison
- Account for heterogeneity (different setups, datasets, seeds)
- Report confidence intervals alongside point estimates
- Use forest plots to visualize cross-study comparisons
- Identify and discuss outliers or inconsistent results
- Consider publication bias when interpreting aggregate results
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- aiming-lab/AutoResearchClaw
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