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trial-sequential-analysis

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Conclusive TSA guidance for meta-analyses.

Education & Research#meta-analysis#heterogeneity#tsa#trial-sequential-analysis#information-size#monitoring-boundaries
Authormatheus-rech
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Trial Sequential Analysis (TSA) helps control type I and II errors in cumulative meta-analyses by applying sequential monitoring boundaries.

Core Features & Use Cases

  • Calculate Required Information Size (RIS) and information fraction to assess evidence sufficiency.
  • Define and interpret monitoring boundaries (benefit, harm, futility) for cumulative data.
  • Generate TSA plots and perform analyses in R using the RTSA package or TSA software to plan future trials.
  • Adjust for heterogeneity and plan evidence-based decisions about continuing or stopping trials.

Quick Start

Input your cumulative meta-analysis data and run a TSA to determine RIS, information fraction, and boundary crossings.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: trial-sequential-analysis
Download link: https://github.com/matheus-rech/meta-agent-mobile/archive/main.zip#trial-sequential-analysis

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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