Full Empirical Analysis Skill R
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics...
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill Full-empirical-analysis-skill-R -g -a claude-code -y- Repository
- brycewang-stanford/Auto-Empirical-Research-Skills4.9k
- Category
- Testing
- Updated
- 6d ago
- License
- See repository
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem, dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid + MatchIt + WeightIt + cobalt + ebal + grf + DoubleML + mediation + marginaleffects + modelsummary + kableExtra + gt + ggplot2 + ggpubr + cowplot + binsreg. **Defaults to economics empirical-paper style** (AER / QJE / AEJ), every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step R pipeline an applied economist runs on every paper, (1) data import & cleaning (read_dta/read_csv, naniar, janitor, validate-merges), (2) variable construction (mutate/across/winsorize/group_by + lag/lead with dplyr), (3) descriptive statistics & Table 1 (gtsummary, modelsummary::datasummary, tableone), (4) classical diagnostic tests (shapiro/jarque.bera.test/bptest/dwtest/bgtest/vif/adf.test/kpss.test/Hausman), (5) baseline modeling (fixest::feols, ivreg, did::att_gt, eventstudyr, sun_ab, did_imputation, synthdid, rdrobust, MatchIt, WeightIt, grf::causal_forest, DoubleML, mediation), (6) robustness battery (modelsummary stack, clubSandwich CRSE, fwildclusterboot, ri2, robomit Oster, bacondecomp, Hon
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.
Companion skills: this is the R sibling of 00-StatsPAI_skill (Python DSL), 00.1-Full-empirical-analysis-skill (explicit Python), and 00.2-Full-empirical-analysis-skill_Stata (Stata .do). All four implement the same 8 steps, in their respective ecosystems.
Philosophy
- Tidyverse + fixest, the modern R idioms.
feols(... | unit + year, cluster = ~unit), not Frankenstein-ylm(y ~ x + factor(unit) + factor(year)). - Reproducible scripts / Quarto. Every example below is paste-runnable.
renvfor package locking;Quarto(.qmd) for combined narrative + code + tables/figures. - 8 steps, first-class. R users historically over-invest in Step 5; this skill treats Steps 1, 4 and 6, 8 as core.
- Rich outputs. Every step yields at least one table or figure, tex/docx/png/pdf.
- Progressive disclosure.
SKILL.mdgives the canonical call per step;references/holds variant-specific depth.
