Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat

In the previous article in this series on common pitfalls in statistical analysis, we looked at the difference between risk and odds. Risk, which refers to the probability of occurrence of an event or outcome, can be defined in absolute or relative terms. Understanding what these measures represent...

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Detalles Bibliográficos
Autores principales: Ranganathan, Priya, Pramesh, C. S., Aggarwal, Rakesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2016
Materias:
Statistics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763519/
https://www.ncbi.nlm.nih.gov/pubmed/26952180
http://dx.doi.org/10.4103/2229-3485.173773
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author Ranganathan, Priya
Pramesh, C. S.
Aggarwal, Rakesh
author_facet Ranganathan, Priya
Pramesh, C. S.
Aggarwal, Rakesh
author_sort Ranganathan, Priya
collection PubMed
description In the previous article in this series on common pitfalls in statistical analysis, we looked at the difference between risk and odds. Risk, which refers to the probability of occurrence of an event or outcome, can be defined in absolute or relative terms. Understanding what these measures represent is essential for the accurate interpretation of study results.
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spelling pubmed-47635192016-03-07 Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat Ranganathan, Priya Pramesh, C. S. Aggarwal, Rakesh Perspect Clin Res Statistics In the previous article in this series on common pitfalls in statistical analysis, we looked at the difference between risk and odds. Risk, which refers to the probability of occurrence of an event or outcome, can be defined in absolute or relative terms. Understanding what these measures represent is essential for the accurate interpretation of study results. Medknow Publications & Media Pvt Ltd 2016 /pmc/articles/PMC4763519/ /pubmed/26952180 http://dx.doi.org/10.4103/2229-3485.173773 Text en Copyright: © 2016 Perspectives in Clinical Research http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Statistics
Ranganathan, Priya
Pramesh, C. S.
Aggarwal, Rakesh
Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat
title Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat
title_full Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat
title_fullStr Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat
title_full_unstemmed Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat
title_short Common pitfalls in statistical analysis: Absolute risk reduction, relative risk reduction, and number needed to treat
title_sort common pitfalls in statistical analysis: absolute risk reduction, relative risk reduction, and number needed to treat
topic Statistics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4763519/
https://www.ncbi.nlm.nih.gov/pubmed/26952180
http://dx.doi.org/10.4103/2229-3485.173773
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