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meta-analysis

Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.

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MIT
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Aug 19, 2026

researchclaw/skills/builtin/experiment/meta-analysis/SKILL.md

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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

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