Data Science & Analytics
Specification Search
Run an instrumented walk of a specification universe and recover honest inference from it. Estimates every specification in a design card (or walks it with a realistic search procedure), logs a complete ledger, flags pathological specifications, calibrates the search against an enforced null, runs the Simonsohn joint tests on the whole curve, measures how far the finding sits from the pre-registered analysis, attributes significance to the choices that produced it, and writes a publishable honest report. Use to run a multiverse or specification-curve analysis, to audit a search someone else ran, to compute multiplicity-corrected or null-calibrated p-values for a selected specification, or to demonstrate how far a search can move a result under a known-zero effect.
- 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
6a61a52201804e485cc6b63c63312c647c66bb9607464ec16d97266906de067f