Critical Values Robust to P-hacking

Adam McCloskey and Pascal Michaillat

Santa Cruz Department of Economics, Working Paper Series from Department of Economics, UC Santa Cruz

Abstract: P-hacking is prevalent in reality but absent from classical hypothesis testing theory. As a consequence, significant results are much more common than they are supposed to be when the null hypothesis is in fact true. In this paper, we build a model of hypothesis testing with p-hacking. From the model, we construct critical values such that, if the values are used to determine significance, and if scientists' p-hacking behavior adjusts to the new significance standards, significant results occur with the desired frequency. Such robust critical values allow for p-hacking so they are larger than classical critical values. To illustrate the amount of correction that p-hacking might require, we calibrate the model using evidence from the medical sciences. In the calibrated model the robust critical value for any test statistic is the classical critical value for the same test statistic with one fifth of the significance level.

Keywords: econ.EM; stat.ME (search for similar items in EconPapers)
Date: 2020-05-08
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.escholarship.org/uc/item/8x77q26c.pdf;origin=repeccitec (application/pdf)

Related works:
Working Paper: Critical Values Robust to P-hacking (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cdl:ucscec:qt8x77q26c

Access Statistics for this paper

More papers in Santa Cruz Department of Economics, Working Paper Series from Department of Economics, UC Santa Cruz Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().