How does it handle study heterogeneity?

It provides tools to calculate Q, I-squared, H-squared, and Tau-squared statistics, along with prediction intervals and subgroup analysis.

Can I calculate effect sizes for binary outcomes?

Yes, the skill provides methods for calculating Odds Ratios (OR), Risk Ratios (RR), Risk Differences (RD), and arcsine transformations.

Can I perform Bayesian meta-analysis with this skill?

Absolutely, it includes implementation patterns for Bayesian random-effects models using the brms package and posterior visualization.

Which R packages does this skill support?

It primarily supports the metafor and meta packages for frequentist analysis, brms for Bayesian models, and MuMIn for multimodel inference.

Does it handle publication bias detection?

Yes, it includes Egger’s regression, Begg’s rank correlation, Trim-and-Fill methods, and Fail-Safe N calculations.

R Meta-Analysis Assistant

Name: R Meta-Analysis Assistant
Author: choxos

bychoxos

0•

Ciencia de Datos y ML

Performs comprehensive pairwise meta-analysis in R using industry-standard libraries like metafor, meta, and brms.

This skill provides specialized guidance for conducting rigorous meta-analyses and evidence synthesis within the R environment. It streamlines the entire statistical workflow, from calculating various effect sizes (SMD, OR, RR, HR) and fitting fixed or random-effects models to assessing heterogeneity and publication bias. Whether you need to generate high-quality forest plots, perform complex meta-regressions, or conduct Bayesian meta-analyses, this skill offers the implementation patterns and best practices required for reproducible biostatistical research.

Características Principales

01Advanced visualization including customized forest, funnel, and Baujat plots

02Effect size calculation for continuous, binary, correlation, and survival data

03Publication bias detection via Egger’s test, Trim-and-Fill, and selection models

04Fixed and random-effects modeling with multiple tau-squared estimators (REML, DL, ML)

05Sensitivity analysis using leave-one-out, influence diagnostics, and cumulative meta-analysis

060 GitHub stars

Casos de Uso

01Investigating study-level moderators through multi-variable meta-regression

02Synthesizing clinical trial data for systematic reviews and evidence-based medicine

03Identifying influential studies and performing Bayesian meta-analyses for complex priors

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add choxos/biostatagent meta-analysis

For use in Claude.ai and ChatGPT