2020/05/08 by Adam McCloskey, Pascal Michaillat · 1 citation
Computer Science · #Parallel Computing and Optimization Techniques #Distributed and Parallel Computing Systems #Service-Oriented Architecture and Web Services
paper · pdf · doi:10.1162/rest_a_01456
Abstract P-hacking is prevalent in reality but absent from classical hypothesis-testing theory. We therefore build a model of hypothesis testing that accounts for p-hacking. From the model, we derive critical values such that, if they are used to determine significance, and if p-hacking adjusts to the new significance standards, then spurious significant results do not occur more often than intended. Because of p-hacking, such robust critical values are larger than classical critical values. In the model calibrated to medical science, the robust critical value is the classical critical value for the same test statistic but with one-fifth of the significance level.