Causal Inference
Determine cause-and-effect relationships using propensity scoring, instrumental variables, and causal graphs for policy evaluation and treatment effects
npx skills add majiayu000/claude-skill-registry --skill causal-inference --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Causal Inference ## Overview Causal inference determines cause-and-effect relationships and estimates treatment effects, going beyond correlation to understand what causes what. ## When to Use - Evaluating the impact of policy interventions or business decisions - Estimating treatment effects when randomized experiments aren't feasible - Controlling for confounding variables in observational data - Determining if a marketing campaign or product change caused an outcome - Analyzing heterogeneous treatment effects across different user segments - Making causal claims from non-experimental data using propensity scores or instrumental variables ## Key Concepts - **Treatment**: Intervention or exposure - **Outcome**: Result or consequence - **Confounding**: Variables affecting both treatment and outcome - **Causal Graph**: Visual representation of relationships - **Treatment Effect**: Impact of intervention - **Selection Bias**: Non-random treatment assignment ## Causal Methods - **Randomized Controlled Trials (RCT)**: Gold standard - **Propensity Score Matching**: Balance treatment/control - **Difference-in-Differences**: Before/after comparison - **Instrumental Variables**: Handle e
- Overview
- When to Use
- Key Concepts
- Causal Methods
- Implementation with Python
- Causal Assumptions
- Treatment Effect Types
- Method Strengths
- Deliverables
What does the Causal Inference skill do?
Determine cause-and-effect relationships using propensity scoring, instrumental variables, and causal graphs for policy evaluation and treatment effects
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill causal-inference --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.