Common pitfalls in statistical analysis: “No evidence of effect” versus “evidence of no effect”

This article is the first in a series exploring common pitfalls in statistical analysis in biomedical research. The power of a clinical trial is the ability to find a difference between treatments, where such a difference exists. At the end of the study, the lack of difference between treatments doe...

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Detalles Bibliográficos
Autores principales: Ranganathan, Priya, Pramesh, C. S., Buyse, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2015
Materias:
Statistics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314850/
https://www.ncbi.nlm.nih.gov/pubmed/25657905
http://dx.doi.org/10.4103/2229-3485.148821
Descripción
Sumario:This article is the first in a series exploring common pitfalls in statistical analysis in biomedical research. The power of a clinical trial is the ability to find a difference between treatments, where such a difference exists. At the end of the study, the lack of difference between treatments does not mean that the treatments can be considered equivalent. The distinction between “no evidence of effect” and “evidence of no effect” needs to be understood.

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