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ipd-meta-analysis

Estimate treatment effects and time-to-event outcomes from participant-level data across studies.

1|Updated Dec 29, 2025
Search Tags:#meta-analysis#survival-analysis#time-to-event#random-effects#ipd#mixed-effects#data-harmonization
One-click install
npx skills add https://github.com/matheus-rech/meta-agent-mobile --skill ipd-meta-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ipd-meta-analysis
Source: https://github.com/matheus-rech/meta-agent-mobile/tree/main/agentskills/ipd-meta-analysis
Command: npx skills add https://github.com/matheus-rech/meta-agent-mobile --skill ipd-meta-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

IPD meta-analysis uses raw participant-level data from multiple studies to provide more precise, flexible analyses than aggregate data, enabling exploration of time-to-event outcomes and treatment-effect modifiers.

Core Features & Use Cases

  • One-stage IPD modeling with hierarchical random effects and flexible covariate adjustment
  • Time-to-event analyses (stratified Cox and frailty models)
  • Exploration of treatment-effect modifiers and missing-data strategies
  • Data harmonization and reproducible workflow across studies

Quick Start

Provide your IPD dataset (study_id, time, event, outcome, treatment, covariates) and request an end-to-end IPD meta-analysis plan.

Frequently Asked Questions about ipd-meta-analysis

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

FAQPage Schema
How do I run an IPD meta-analysis with patient-level survival data?▼

To run an IPD meta-analysis with survival data, provide a dataset containing study_id, time, event, treatment, and covariates to apply stratified Cox or frailty models within a one-stage mixed-effects framework.

What is the difference between one-stage and two-stage IPD meta-analysis?▼

A one-stage IPD meta-analysis models raw participant-level data simultaneously using hierarchical random effects, whereas a two-stage approach analyzes studies separately before combining the estimates.

When do I need individual participant data for a meta-analysis instead of aggregate data?▼

You need individual participant data when you want to investigate treatment-effect modifiers, explore time-to-event outcomes, or apply missing-data strategies that aggregate data cannot provide.

How do I handle missing data in an IPD meta-analysis?▼

Handle missing data in an IPD meta-analysis by applying integrated missing-data strategies within your reproducible workflow across the harmonized participant-level datasets from multiple trials.

Can I use mixed-effects models to identify treatment-effect modifiers across multiple trials?▼

Yes, you can use one-stage mixed-effects models on harmonized individual participant data to explore and estimate treatment-effect modifiers across multiple studies in your meta-analysis.

What data format is required to start a time-to-event meta-analysis?▼

To start a time-to-event meta-analysis, you need a raw participant-level dataset structured with study_id, time, event, outcome, treatment, and relevant covariates for data harmonization.

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