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meta-analysis

Compute Bayesian meta-analysis with Stan and JAGS across fixed and random effects.

9|1|Updated Jan 10, 2026
Search Tags:#meta-analysis#bayesian#stan#fixed-effects#random-effects#network-meta-analysis#jags
One-click install
npx skills add https://github.com/choxos/BiostatAgent --skill meta-analysis-choxos
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: meta-analysis
Source: https://github.com/choxos/BiostatAgent/tree/main/plugins/bayesian-modeling/skills/meta-analysis
Command: npx skills add https://github.com/choxos/BiostatAgent --skill meta-analysis-choxos

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Consolidates evidence from multiple studies by enabling Bayesian meta-analysis across fixed effects, random effects, and network meta-analysis using Stan and JAGS.

Core Features & Use Cases

  • Fixed-effects and random-effects meta-analysis modeling with Stan and JAGS
  • Network meta-analysis capability with treatment hierarchy and ranking
  • Posterior summaries, heterogeneity assessment, and credible intervals for decision-making
  • Reproducible workflows for combining diverse study data

Quick Start

Fit a Bayesian meta-analysis by supplying study estimates and standard errors, then review posterior results.

Frequently Asked Questions about meta-analysis

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

FAQPage Schema
How do I run a Bayesian meta-analysis on clinical trial data?▼

Run a Bayesian meta-analysis by supplying clinical trial study estimates and standard errors to the Skill, which then uses Stan or JAGS to compute posterior summaries and heterogeneity assessments.

What is the difference between fixed-effects and random-effects meta-analysis in Stan?▼

Fixed-effects meta-analysis assumes a single true effect across studies, while random-effects meta-analysis accounts for heterogeneity between studies using Stan or JAGS to model varying true effects.

Do I need Stan or JAGS installed to perform network meta-analysis?▼

Yes, you need either Stan or JAGS installed as a backend, because the Skill requires these probabilistic programming frameworks to compute posterior estimates and treatment rankings for network meta-analysis.

Can I use Bayesian meta-analysis for diagnostic accuracy datasets?▼

Yes, Bayesian meta-analysis is applicable to diagnostic accuracy datasets, as well as syntheses of clinical trials and observational studies, producing posterior summaries and credible intervals for decision-making.

How do I assess heterogeneity in a Bayesian random-effects meta-analysis?▼

Assess heterogeneity in a Bayesian random-effects meta-analysis by reviewing posterior summaries and credible intervals computed by the Skill, which models varying true effects across studies using Stan or JAGS.

What is the best way to rank treatments in a network meta-analysis?▼

Rank treatments in a network meta-analysis by providing study-level effect sizes and standard errors to the Skill, which computes treatment hierarchies and rankings using Bayesian posterior estimates via Stan or JAGS.

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