forest-plot-creation

Generate forest plots from yi and sei using metafor package in R.

1|Updated Dec 29, 2025

Search Tags:#r #meta-analysis #data-visualization #statistical-analysis #metafor #forest-plot

Ready to run

npx skills add https://github.com/matheus-rech/meta-agent-mobile --skill forest-plot-creation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: forest-plot-creation
Source: https://github.com/matheus-rech/meta-agent-mobile/tree/main/agentskills/forest-plot-creation
Command: npx skills add https://github.com/matheus-rech/meta-agent-mobile --skill forest-plot-creation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Forest plots are essential for visualizing meta-analysis results, showing study effects, weights, and confidence intervals at a glance. This skill provides clear guidance on constructing and understanding these plots to facilitate interpretation and communication of meta-analytic findings.

Core Features & Use Cases

Visualization: Generate forest plots representing individual study effects, weights, and CIs.
Interpretation Guidance: Explain how to read the plot, identify the line of no effect, and assess heterogeneity visually.
Customization: Support subgroups, subgroup labels, and model-type notes for transparent reporting.
Use Case: A researcher wants to present a random-effects meta-analysis of several RCTs in a manuscript figure.

Quick Start

Provide a dataset containing yi and sei values to generate a forest plot.

Frequently Asked Questions about forest-plot-creation

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

FAQPage Schema

How do I create a forest plot for a random-effects meta-analysis in R?▼

To create a forest plot in R, you need a dataset containing study effect sizes (yi) and standard errors (sei) to fit a random-effects model using the metafor package. This Skill guides you through generating the plot and customizing it with subgroup labels.

What data do I need to generate a forest plot with the metafor package?▼

You need a dataset containing yi (effect sizes) and sei (standard errors) values to generate a forest plot with the metafor package. Providing these inputs allows the Skill to visualize study effects, weights, and confidence intervals across your meta-analysis.

Can I customize forest plots to show subgroups and model-type notes?▼

Yes, you can customize forest plots to display subgroups, subgroup labels, and model-type notes for transparent reporting. This ensures your visualization clearly communicates heterogeneity and random-effects model details for manuscript figures.

How do I interpret heterogeneity and the line of no effect on a forest plot?▼

To interpret a forest plot, this Skill explains how to read the plot, identify the line of no effect, and visually assess heterogeneity across studies. It helps you understand individual study weights and confidence intervals at a glance.

Do I need R and the metafor package installed to visualize meta-analysis results?▼

Yes, you need R with the metafor package installed to produce and customize forest plots. This Skill requires your input data, a fitted random-effects model, and this environment to visualize your statistical analysis results effectively.