meta-analysis-guide
Installation
SKILL.md
Meta-Analysis Guide
A skill for conducting rigorous meta-analyses: computing and pooling effect sizes, assessing heterogeneity, evaluating publication bias, and generating forest plots. Follows Cochrane Handbook and PRISMA guidelines.
Effect Size Computation
Common Effect Size Measures
| Measure | Use Case | Formula | Interpretation |
|---|---|---|---|
| Cohen's d | Mean difference (2 groups) | (M1 - M2) / S_pooled | 0.2 small, 0.5 medium, 0.8 large |
| Hedges' g | d with small-sample correction | d * J(df) | Preferred over d for small N |
| Pearson r | Correlation | r | 0.1 small, 0.3 medium, 0.5 large |
| Odds Ratio | Binary outcomes | (ad)/(bc) | 1 = no effect |
| Risk Ratio | Binary outcomes | (a/(a+b))/(c/(c+d)) | 1 = no effect |
| SMD | Standardized mean difference | Same as Hedges' g | When scales differ |
Computing Effect Sizes in Python
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