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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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Overview

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

Install command

npx skills add https://github.com/aiming-lab/AutoResearchClaw --skill meta-analysis

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Source

aiming-lab/AutoResearchClaw

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Forks1,534

UpdatedMarch 23, 2026 at 01:46

SKILL.md

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name	meta-analysis
description	Statistical methods for combining results across multiple studies. Use when aggregating cross-study or cross-experiment results.
metadata	{"category":"experiment","trigger-keywords":"meta-analysis,effect size,pooled,cross-study,aggregat","applicable-stages":"7,14","priority":"5","version":"1.0","author":"researchclaw","references":"Borenstein et al., Introduction to Meta-Analysis, 2009"}

Meta-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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Source

aiming-lab

aiming-lab/AutoResearchClaw

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Useful forSOC

Operations Research AnalystsComputer and Mathematical Occupations15-2031L4

StatisticiansL4

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