Full Empirical Analysis R

Full Empirical Analysis R is a Data skill for Claude Code, published by brycewang-stanford in Auto-Empirical-Research-Skills.

3.4K stars445 forkson brycewang-stanford/Auto-Empirical-Research-SkillsAdded 2026/08/16+1% in starsRepository updated 2026/08/10

View source on GitHub Download repo ZIP

academic-researchagent-skillsai-agentawesome-listcommunicationcopapereconomicseducationempirical-researchinternational-relationspolitical-sciencepsychologypublic-administrationreproducible-researchskills-librarysocial-sciencesociology

Install in seconds

Install Full Empirical Analysis R

Copy Full Empirical Analysis R into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/00.3-Full-empirical-analysis-skill_R ~/.claude/skills/00.3-Full-empirical-analysis-skill_R

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/00.3-Full-empirical-analysis-skill_R/SKILL.md in brycewang-stanford/Auto-Empirical-Research-Skills
Installs to: ~/.claude/skills/00.3-Full-empirical-analysis-skill_R
Collection: One of 25 skills cataloged from this repository
Category: Data — 668 skills

What Full Empirical Analysis R does

Full Empirical Analysis R runs a complete 8-step empirical research pipeline in R using tidyverse and econometrics packages, generating publication-ready regression tables, descriptive statistics, robustness checks, and figures for applied economics, epidemiology, and ML causal inference.

Full Empirical Analysis R is cataloged under Data on DirSkills. Full Empirical Analysis R comes from a repository tagged academic-research, agent-skills, ai-agent, awesome-list and communication.

Documentation

README

Excerpt

Full Empirical Analysis — Classical R Workflow

This skill is the canonical 8-step pipeline an applied economist runs on every empirical paper, written in the modern tidyverse + econometrics R ecosystem — dplyr/tidyr/haven for data, fixest as the panel/IV/DID workhorse, did/bacondecomp/HonestDiD for modern DID, rdrobust/rddensity for RD, Synth/gsynth/synthdid for synthetic control, MatchIt/WeightIt/cobalt/ebal for matching, grf/DoubleML for ML causal, mediation for causal mediation, marginaleffects for post-estimation, modelsummary/kableExtra/gt for publication tables, ggplot2/iplot/binsreg for figures.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Full Empirical Analysis R

What else does brycewang-stanford publish alongside Full Empirical Analysis R?
Full Empirical Analysis R 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 Full Empirical Analysis R 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.
How does Full Empirical Analysis R compare to other Data skills?
Full Empirical Analysis R ranks #202 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 Full Empirical Analysis R against them. Open each page to compare what they document and how they install.