Data Science & Analytics
Phack Polyglot
Run the instrumented specification search in the user's own statistical language — Stata (reghdfe, ivreghdfe, rdrobust, did2s), R (fixest, rdrobust, did2s), Python (statsmodels, linearmodels) or StatsPAI — and bring the results back into the audit, null calibration and honest report. Exports the enumerated grid as a language-neutral specs table plus a generated runner, ingests the runner's ledger, replays the null draws in that language, and reports cross-language parity. Use when an analysis or an agent evaluation must happen in Stata, R or StatsPAI rather than the Python engine, when a p-hacked result was produced in one of those languages and needs auditing on its own footing, when reading Stata / R / StatsPAI code for search and disclosure signals, or when checking that the engine's numbers agree with a reference implementation.
- Publisher / source
- brycewang-stanford/Auto-Empirical-Research-Skills (found on GitHub top repositories)
- Upstream record
- brycewang-stanford/Auto-Empirical-Research-Skills
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
a9aa1e39d136cdb51c941167d214406dea26a2512d7c42ad4a46145770a751b5