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The misuse and abuse of statistics in biomedical research

Statistics are the primary tools for assessing relationships and evaluating study questions. Unfortunately, these tools are often misused, either inadvertently because of ignorance or lack of planning, or conspicuously to achieve a specified result. Data abuses include the incorrect application of s...

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Detalles Bibliográficos
Autores principales: Thiese, Matthew S., Arnold, Zachary C., Walker, Skyler D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Croatian Society of Medical Biochemistry and Laboratory Medicine 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401313/
https://www.ncbi.nlm.nih.gov/pubmed/25672462
http://dx.doi.org/10.11613/BM.2015.001
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author Thiese, Matthew S.
Arnold, Zachary C.
Walker, Skyler D.
author_facet Thiese, Matthew S.
Arnold, Zachary C.
Walker, Skyler D.
author_sort Thiese, Matthew S.
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description Statistics are the primary tools for assessing relationships and evaluating study questions. Unfortunately, these tools are often misused, either inadvertently because of ignorance or lack of planning, or conspicuously to achieve a specified result. Data abuses include the incorrect application of statistical tests, lack of transparency and disclosure about decisions that are made, incomplete or incorrect multivariate model building, or exclusion of outliers. Individually, each of these actions may completely invalidate a study, and often studies are victim to more than one offense. Increasingly there are tools and guidance for researchers to look to, including the development of an analysis plan and a series of study specific checklists, in order to prevent or mitigate these offenses.
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spelling pubmed-44013132015-04-24 The misuse and abuse of statistics in biomedical research Thiese, Matthew S. Arnold, Zachary C. Walker, Skyler D. Biochem Med (Zagreb) Review Article Statistics are the primary tools for assessing relationships and evaluating study questions. Unfortunately, these tools are often misused, either inadvertently because of ignorance or lack of planning, or conspicuously to achieve a specified result. Data abuses include the incorrect application of statistical tests, lack of transparency and disclosure about decisions that are made, incomplete or incorrect multivariate model building, or exclusion of outliers. Individually, each of these actions may completely invalidate a study, and often studies are victim to more than one offense. Increasingly there are tools and guidance for researchers to look to, including the development of an analysis plan and a series of study specific checklists, in order to prevent or mitigate these offenses. Croatian Society of Medical Biochemistry and Laboratory Medicine 2015-02-15 /pmc/articles/PMC4401313/ /pubmed/25672462 http://dx.doi.org/10.11613/BM.2015.001 Text en
spellingShingle Review Article
Thiese, Matthew S.
Arnold, Zachary C.
Walker, Skyler D.
The misuse and abuse of statistics in biomedical research
title The misuse and abuse of statistics in biomedical research
title_full The misuse and abuse of statistics in biomedical research
title_fullStr The misuse and abuse of statistics in biomedical research
title_full_unstemmed The misuse and abuse of statistics in biomedical research
title_short The misuse and abuse of statistics in biomedical research
title_sort misuse and abuse of statistics in biomedical research
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401313/
https://www.ncbi.nlm.nih.gov/pubmed/25672462
http://dx.doi.org/10.11613/BM.2015.001
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