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Getting it right matters! Covid‐19 pandemic analogies to everyday life in medical sciences.

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Title: Getting it right matters! Covid‐19 pandemic analogies to everyday life in medical sciences.
Authors: Bothe, Tomas L. (AUTHOR), Patzak, Andreas (AUTHOR), Schubert, Rudolf (AUTHOR), Pilz, Niklas (AUTHOR)
Source: Acta Physiologica. Sep2021, Vol. 233 Issue 1, p1-5. 5p. 2 Diagrams.
Subjects: COVID-19 pandemic, Medical sciences, Life sciences, Everyday life, Statistical power analysis
Abstract: To reduce the occurrence of false positive results, the scientific community has taken measures such as reporting the I P i value of statistical tests and assumed power in study design. A power of at least 0.8 helps tremendously to keep inflating effect sizes and false positive results in check. It is very unlikely for you to be one of the false negative results and even if you had been tested positive, your chance of actually being infected would only have been around 3.8% (3960 true positives/(3960 true positives + 99 600 false positives), because of a large number of false positives. In other words: The false positive risk of your test is at about 96.2% (99 600 false positives/(3960 true positives + 99 600 false positives). [Extracted from the article]
Copyright of Acta Physiologica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Getting it right matters! Covid‐19 pandemic analogies to everyday life in medical sciences.
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  Data: <searchLink fieldCode="AR" term="%22Bothe%2C+Tomas+L%2E%22">Bothe, Tomas L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Patzak%2C+Andreas%22">Patzak, Andreas</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schubert%2C+Rudolf%22">Schubert, Rudolf</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pilz%2C+Niklas%22">Pilz, Niklas</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Acta+Physiologica%22">Acta Physiologica</searchLink>. Sep2021, Vol. 233 Issue 1, p1-5. 5p. 2 Diagrams.
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  Data: <searchLink fieldCode="DE" term="%22COVID-19+pandemic%22">COVID-19 pandemic</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+sciences%22">Medical sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Life+sciences%22">Life sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Everyday+life%22">Everyday life</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+power+analysis%22">Statistical power analysis</searchLink>
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  Label: Abstract
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  Data: To reduce the occurrence of false positive results, the scientific community has taken measures such as reporting the I P i value of statistical tests and assumed power in study design. A power of at least 0.8 helps tremendously to keep inflating effect sizes and false positive results in check. It is very unlikely for you to be one of the false negative results and even if you had been tested positive, your chance of actually being infected would only have been around 3.8% (3960 true positives/(3960 true positives + 99 600 false positives), because of a large number of false positives. In other words: The false positive risk of your test is at about 96.2% (99 600 false positives/(3960 true positives + 99 600 false positives). [Extracted from the article]
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  Label:
  Group: Ab
  Data: <i>Copyright of Acta Physiologica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/apha.13714
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        Text: English
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      – SubjectFull: Life sciences
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      – SubjectFull: Statistical power analysis
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              M: 09
              Text: Sep2021
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              Y: 2021
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