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Significance testing as perverse probabilistic reasoning
Truth claims in the medical literature rely heavily on statistical significance testing. Unfortunately, most physicians misunderstand the underlying probabilistic logic of significance tests and consequently often misinterpret their results. This near-universal misunderstanding is highlighted by mea...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2011
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3058025/ https://www.ncbi.nlm.nih.gov/pubmed/21356064 http://dx.doi.org/10.1186/1741-7015-9-20 |
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author | Westover, M Brandon Westover, Kenneth D Bianchi, Matt T |
author_facet | Westover, M Brandon Westover, Kenneth D Bianchi, Matt T |
author_sort | Westover, M Brandon |
collection | PubMed |
description | Truth claims in the medical literature rely heavily on statistical significance testing. Unfortunately, most physicians misunderstand the underlying probabilistic logic of significance tests and consequently often misinterpret their results. This near-universal misunderstanding is highlighted by means of a simple quiz which we administered to 246 physicians at two major academic hospitals, on which the proportion of incorrect responses exceeded 90%. A solid understanding of the fundamental concepts of probability theory is becoming essential to the rational interpretation of medical information. This essay provides a technically sound review of these concepts that is accessible to a medical audience. We also briefly review the debate in the cognitive sciences regarding physicians' aptitude for probabilistic inference. |
format | Text |
id | pubmed-3058025 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30580252011-03-17 Significance testing as perverse probabilistic reasoning Westover, M Brandon Westover, Kenneth D Bianchi, Matt T BMC Med Debate Truth claims in the medical literature rely heavily on statistical significance testing. Unfortunately, most physicians misunderstand the underlying probabilistic logic of significance tests and consequently often misinterpret their results. This near-universal misunderstanding is highlighted by means of a simple quiz which we administered to 246 physicians at two major academic hospitals, on which the proportion of incorrect responses exceeded 90%. A solid understanding of the fundamental concepts of probability theory is becoming essential to the rational interpretation of medical information. This essay provides a technically sound review of these concepts that is accessible to a medical audience. We also briefly review the debate in the cognitive sciences regarding physicians' aptitude for probabilistic inference. BioMed Central 2011-02-28 /pmc/articles/PMC3058025/ /pubmed/21356064 http://dx.doi.org/10.1186/1741-7015-9-20 Text en Copyright ©2011 Westover et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Debate Westover, M Brandon Westover, Kenneth D Bianchi, Matt T Significance testing as perverse probabilistic reasoning |
title | Significance testing as perverse probabilistic reasoning |
title_full | Significance testing as perverse probabilistic reasoning |
title_fullStr | Significance testing as perverse probabilistic reasoning |
title_full_unstemmed | Significance testing as perverse probabilistic reasoning |
title_short | Significance testing as perverse probabilistic reasoning |
title_sort | significance testing as perverse probabilistic reasoning |
topic | Debate |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3058025/ https://www.ncbi.nlm.nih.gov/pubmed/21356064 http://dx.doi.org/10.1186/1741-7015-9-20 |
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