Year: 2023
Type: article
Abstract: Recent research proposed an efficient way of streamlining p-hacking: a metric of randomly generated p-values that always indicates significant results (p-ointless). However, the metric’s applicability is limited, since it covers only a very small range of use cases that are relevant for p-hacking researchers. To address this issue, we present extra p-ointless, a new metric that allows researchers to freely specify desired p-value ranges while safeguarding full reproducibility. Our newly introduced extra p-ointless metric not only addresses the limitations of the original metric but also answers editors’ and reviewers’ calls for alternative and innovative statistical approaches. An R-based, interactive shiny web app helps researchers with little background in coding to apply our metric.
Source: Journal of Business Research
Authors: Marko Sarstedt, Susanne J. Adler
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4365505697