Data Science & Analytics
Phack Detection
Test whether a body of reported results shows p-hacking, selective reporting or selection between stages, using the p-curve battery and the threshold and across-stages tests of Adda, Decker and Ottaviani (2020). Implements the binomial, Fisher, Stouffer and least-concave-majorant monotonicity tests of Elliott, Kudrin and Wuethrich (2022); threshold-bunching tests calibrated against a smooth counterfactual density; a Cattaneo-Jansson-Ma density-jump test and a right-side spike test that tell a level shift (results withheld) from a spike (results pushed across); the phase II vs phase III comparison and the selective-continuation decomposition; and Simonsohn's p-curve power estimate. Use when asked whether a literature, a journal, a research design, an author, a registry or a set of agent runs shows evidence of p-hacking, publication bias or selective continuation.
- 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
1b25d2a7e5aaec1173fe5ccb660a5ae4562e9a0a721201dc9e92fe10937b9fc1