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designing-experiments

pymc-labs
Updated 29 days ago
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About

This skill helps developers select the correct quasi-experimental method (DiD, ITS, or SC) for causal inference based on their data structure. It provides a clear decision framework that considers the presence of a control group and the unit/time dimensions of the dataset. Use it when you have observational data and are unsure which analytical method to apply.

Quick Install

Claude Code

Recommended
Primary
npx skills add pymc-labs/CausalPy -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/pymc-labs/CausalPy
Git CloneAlternative
git clone https://github.com/pymc-labs/CausalPy.git ~/.claude/skills/designing-experiments

Copy and paste this command in Claude Code to install this skill

GitHub Repository

pymc-labs/CausalPy
Path: .claude/skills/designing-experiments
0
causal-inferencepymcquasi-experimentalquasi-experiments

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