designing-experiments
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
Recommendednpx skills add pymc-labs/CausalPy -a claude-code/plugin add https://github.com/pymc-labs/CausalPygit clone https://github.com/pymc-labs/CausalPy.git ~/.claude/skills/designing-experimentsCopy and paste this command in Claude Code to install this skill
GitHub Repository
Frequently asked questions
What is the designing-experiments skill?
designing-experiments is a Claude Skill by pymc-labs. Skills package instructions and resources that Claude loads on demand, so Claude can perform designing-experiments-related tasks without extra prompting.
How do I install designing-experiments?
Use the install commands on this page: add designing-experiments to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does designing-experiments belong to?
designing-experiments is in the Design category, tagged design and data.
Is designing-experiments free to use?
Yes. designing-experiments is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
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