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causal-inference

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Master causal inference methods.

Data & Analytics#diagnostics#causal-inference#did#iv#rdd#synthetic-control
AuthorJames-Traina
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps researchers identify causal effects from observational data by outlining methodological frameworks, identification arguments, and estimation strategies across common quasi-experimental designs.

Core Features & Use Cases

  • Identification strategies: IV/2SLS, DiD, RDD, synthetic control, and matching.
  • Diagnostics & robustness: Pre-trends checks, overidentification tests, and sensitivity analyses.
  • Use Case: A policy evaluator uses DiD with staggered adoption to estimate treatment effects while checking for parallel trends and robustness.

Quick Start

Provide a causal research question and data, then choose an identification strategy (IV/2SLS, DiD, or RDD) and run diagnostics.

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: causal-inference
Download link: https://github.com/James-Traina/compound-science/archive/main.zip#causal-inference

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