causal-inference-mixtape
This skill should be used when the user asks to "implement a DiD regression", "write a causal inference pipeline", "set up an event study", "implement instrumental variables", "run a regression discontinuity design", "build a synthetic control model", "implement propensity score matching", "write parallel trends test", "implement Bacon decomposition", or needs code templates for causal inference methods in Python, R, or Stata. Based on Scott Cunningham''s Causal Inference: The Mixtape.
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill 10-Jill0099-causal-inference-mixtape --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: The Mixtape — Code Skill Practitioner-oriented causal inference skill built from Scott Cunningham's *Causal Inference: The Mixtape* repository. Covers 10 identification strategies with ready-to-run code templates in Python, R, and Stata. --- ## Methods Covered | Method | Python | R | Stata | Reference | |--------|--------|---|-------|-----------| | OLS / Regression | statsmodel
What does the causal-inference-mixtape skill do?
This skill should be used when the user asks to "implement a DiD regression", "write a causal inference pipeline", "set up an event study", "implement instrumental variables", "run a regression discontinuity design", "build a synthetic control model", "implement propensity score matching", "write parallel trends test", "implement Bacon decomposition", or needs code templates for causal inference methods in Python, R, or Stata. Based on Scott Cunningham''s Causal Inference: The Mixtape.
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill 10-Jill0099-causal-inference-mixtape --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 brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 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.