meta_analysis

Pool effect sizes from clinical studies into a single estimate with I².

1|Updated Mar 23, 2026
One-click install
npx skills add https://github.com/hellonish/singularity --skill meta-analysis-hellonish
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: meta_analysis
Source: https://github.com/hellonish/singularity/tree/main/SKILLS/tier2_analysis/meta_analysis
Command: npx skills add https://github.com/hellonish/singularity --skill meta-analysis-hellonish

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Meta-analysis consolidates results from multiple clinical studies to provide a precise, overall estimate of effect size, reducing uncertainty from individual studies.

Core Features & Use Cases

  • Input: structured list of studies with study_id, effect_size, ci_lower, ci_upper
  • Compute pooled effect when there are 3 or more comparable studies
  • Compute heterogeneity (I²)
  • If fewer than 3 studies: return insufficient_studies: true — do NOT compute a pooled estimate
  • Prerequisites: upstream data extraction assistant providing clean data
  • Produces forest-plot-ready data and supports downstream reporting

Quick Start

Provide a structured array of studies (study_id, effect_size, ci_lower, ci_upper); the skill will compute the pooled effect, heterogeneity, and forest-plot data.

Frequently Asked Questions about meta_analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I pool effect sizes from multiple clinical studies into a single estimate?▼

A meta-analysis combines numerical results from multiple clinical studies to produce a single pooled effect estimate, reducing the uncertainty inherent in individual study findings.

What is the minimum number of studies required for statistical pooling?▼

Statistical pooling requires 3 or more comparable clinical studies. If fewer are provided, the tool returns insufficient_studies: true and does not compute a pooled estimate.

Can I compute heterogeneity and forest plot data for my evidence synthesis?▼

Evidence synthesis outputs include the I² heterogeneity statistic and forest-plot-ready data when you input 3 or more comparable studies with valid confidence intervals.

Does meta-analysis support both fixed-effects and random-effects pooling models?▼

The meta-analysis supports both fixed-effects and random-effects pooling models to synthesize clinical study results, letting you choose the appropriate statistical method for your data.

What format should study data be in for clinical evidence synthesis?▼

Clinical evidence synthesis requires a structured input array where each study record includes a study_id, effect_size, ci_lower, and ci_upper to perform validation and compute the pooled estimate.