Extreme undisclosed analytical flexibility in HRV with automated p‐mining software

Department of Psychology, University of Sydney, Sydney, Australia
DOI
10.7287/peerj.preprints.277v1
Subject Areas
Psychiatry and Psychology, Science Policy
Keywords
heart rate variability, HRV
Copyright
© 2014 Heathers et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Heathers JA, Holcombe AO. 2014. Extreme undisclosed analytical flexibility in HRV with automated p‐mining software. PeerJ PrePrints 2:e277v1

Abstract

Heart rate variability (HRV) is the study of the beat‐to‐beat variability in the heart rate, which is a consequence of the immediate state of the autonomic nervous system. While it is a popular psychobiological technique, flexibility within analytical methods allows any finding to be presented as significant.Here we present a potential demonstration of this, by automating analytical decisions to manipulate findings into significance by automating an extreme number of different yet plausible paths for analysis (PMinerEKG).It should be possible to demonstrate ‘extremely significant’ ‐ and entirely spurious ‐ differences between even extremely similar datasets simply by performing enough analyses.

Author Comment

This is a pre-registration of a paper to be prepared, consistent with the Open Science framework: https://osf.io/tvyxz/wiki/home/