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The Extent and Consequences of P-Hacking in Science

Head, Megan L.; Holman, Luke; Lanfear, Rob; Kahn, Andrew T.; Jennions, Michael D.


A focus on novel, confirmatory, and statistically significant results leads to substantial bias in the scientific literature. One type of bias, known as "p-hacking," occurs when researchers collect or select data or statistical analyses until nonsignificant results become significant. Here, we use text-mining to demonstrate that p-hacking is widespread throughout science. We then illustrate how one can test for p-hacking when performing a meta-analysis and show that, while p-hacking is probably...[Show more]

CollectionsANU Research Publications
Date published: 2015-03-13
Type: Journal article
Source: PLOS Biology
DOI: 10.1371/journal.pbio.1002106


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