Open Accessmethod to streamline p-hacking
Author(s) -
Ian Hussey
Publication year - 2021
Publication title -
meta-psychology
Language(s) - English
Resource type - Journals
ISSN - 2003-2714
DOI - 10.15626/mp.2020.2529
Subject(s) - hacker , statistical inference , order (exchange) , inference , process (computing) , computer science , modal , replication (statistics) , psychology , data science , computer security , statistics , business , artificial intelligence , mathematics , finance , chemistry , polymer chemistry , operating system
The analytic strategy of p-hacking has rapidly accelerated the achievement of psychological scientists’ goals (e.g., publications & tenure), but has suffered a number of setbacks in recent years. In order to remediate this, this article presents a statistical inference measure that can greatly accelerate and streamline the p-hacking process: generating random numbers that are < .05. I refer to this approach as pointless. Results of a simulation study are presented and an R script is provided for others to use. In the absence of systemic changes to modal p-hacking practices within psychological science (e.g., worrying trends such as preregistration and replication), I argue that vast amounts of time and research funding could be saved through the widespread adoption of this innovative approach.