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maic-methodology

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Deep MAIC guidance for robust ITC analyses.

Data & Analytics#anchored#ess#maic#indirect-comparison#itc#covariate-selection#weight-diagnostics
Authorchoxos
Version1.0.0
Installs0

System Documentation

What problem does it solve?

MAIC methodology guidance provides structured support for conducting and reviewing Matching-Adjusted Indirect Comparisons, helping analysts decide when MAIC is appropriate, select covariates, and interpret weight diagnostics.

Core Features & Use Cases

  • Method selection guidance: Decide anchored vs unanchored MAIC and justify methodological choices based on data.
  • Covariate selection & overlap checks: Recommend covariates, assess overlap, and monitor ESS.
  • Interpretation & reporting templates: Provide checklists and templates for transparent reporting of methods and results.
  • Example: Suppose IPD is available for one trial and only aggregate data for a comparator; MAIC can be used to align populations and estimate the indirect comparison.

Quick Start

Provide a step-by-step MAIC plan for a given IPD-AgD pair, including covariate selection, weighting strategy, and reporting format.

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: maic-methodology
Download link: https://github.com/choxos/ITC-agents/archive/main.zip#maic-methodology

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