Causal Inference Mixtape is a Data skill for Claude Code, published by brycewang-stanford in Auto-Empirical-Research-Skills.
Causal Inference Mixtape provides code templates for 10 causal inference identification strategies in Python, R, and Stata. Use it to implement DiD, event studies, IV, RDD, synthetic control, matching, and robustness checks.
Causal Inference Mixtape is cataloged under Data on DirSkills. Causal Inference Mixtape comes from a repository tagged academic-research, agent-skills, ai-agent, awesome-list and communication.
Documentation
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.
This is the opening of the README. Read the full README on GitHub.
Causal Inference Mixtape is one of 25 skills that DirSkills catalogs from brycewang-stanford/Auto-Empirical-Research-Skills, the repository it ships in. Its siblings there include Academic Paper Composer, Academic Proofreader and Auto-Empirical Research. Each one is a separate skill with its own page in this directory, installs the same way Causal Inference Mixtape does, and is maintained by brycewang-stanford in that same repository. The rest of the collection is listed on the brycewang-stanford/Auto-Empirical-Research-Skills page.
Causal Inference Mixtape ranks #200 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Causal Inference Mixtape against them. Open each page to compare what they document and how they install.
Causal Inference Mixtape is one of 25 skills cataloged on DirSkills from brycewang-stanford/Auto-Empirical-Research-Skills.
Causal Inference Mixtape is one of 668 Data skills cataloged on DirSkills, ranked #200 by stars among them.