CORP: Minimizing the chances of false positives and false negatives
Author(s) -
Douglas CurranEverett
Publication year - 2016
Publication title -
journal of applied physiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.253
H-Index - 229
eISSN - 8750-7587
pISSN - 1522-1601
DOI - 10.1152/japplphysiol.00937.2016
Subject(s) - false positive paradox , false positives and false negatives , medicine , computer science , artificial intelligence
Statistics is essential to the process of scientific discovery. An inescapable tenet of statistics, however, is the notion of uncertainty which has reared its head within the arena of reproducibility of research. The Journal of Applied Physiology's recent initiative, "Cores of Reproducibility in Physiology," is designed to improve the reproducibility of research: each article is designed to elucidate the principles and nuances of using some piece of scientific equipment or some experimental technique so that other researchers can obtain reproducible results. But other researchers can use some piece of equipment or some technique with expert skill and still fail to replicate an experimental result if they neglect to consider the fundamental concepts of statistics of hypothesis testing and estimation and their inescapable connection to the reproducibility of research. If we want to improve the reproducibility of our research, then we want to minimize the chance that we get a false positive and-at the same time-we want to minimize the chance that we get a false negative. In this review I outline strategies to accomplish each of these things. These strategies are related intimately to fundamental concepts of statistics and the inherent uncertainty embedded in them.
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