AI agent skill · by @aiming-lab

Meta Analysis

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

Data Analysis

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Archived 2026-10-23 · Source updated 2026-08-19 · License: MIT. Check the original repository for the latest version.

SKILL.md instructions

## 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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