Data Science & Analytics
Phack Taxonomy
Name and classify p-hacking strategies, and quantify what each one does to the false-positive rate. Covers the twelve-strategy compendium of Stefan and Schoenbrodt (2023), thirteen econometrics-specific degrees of freedom (clustering doctrine, fixed-effect structure, RDD bandwidth, kernel and inference mode, IV instrument sets and first-stage screening, staggered-DiD estimator and comparison-group choice, synthetic-control donor pools), the search procedures that turn a strategy into a session, and the two between-stage strategies of Adda, Decker and Ottaviani (2020): selective continuation from a pilot to a confirmatory study, which is not p-hacking until the pilot is pooled, and selective reporting between stages. Use when asked what p-hacking is, which strategy a particular analytical choice corresponds to, how much a given researcher degree of freedom inflates type I error, or to enumerate the ways a specific result could have been obtained.
- 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
43c9dd7c039613de85b901cf397f5c0b9d6c863ec73ff2561c38405f1302ef22