Open AccessCommon pitfalls in statistical analysis: "No evidence of effect" versus "evidence of no effect"
Author(s) -
Priya Ranganathan,
C S Pramesh,
Marc Buyse
Publication year - 2015
Publication title -
perspectives in clinical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.649
H-Index - 8
eISSN - 2229-5488
pISSN - 2229-3485
DOI - 10.4103/2229-3485.148821
Subject(s) - statistical evidence , statistical analysis , evidence based medicine , treatment effect , significant difference , medicine , econometrics , statistics , psychology , alternative medicine , mathematics , traditional medicine , null hypothesis , pathology
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.