Insights in Hypothesis Testing and Making Decisions in Biomedical Research
Varin Sacha1, Demosthenes B. Panagiotakos2, *
Identifiers and Pagination:Year: 2016
First Page: 196
Last Page: 200
Publisher ID: TOCMJ-10-196
Article History:Received Date: 2/12/2015
Revision Received Date: 22/2/2016
Acceptance Date: 5/3/2016
Electronic publication date: 30/09/2016
Collection year: 2016
open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
It is a fact that p values are commonly used for inference in biomedical and other social fields of research. Unfortunately, the role of p value is very often misused and misinterpreted; that is why it has been recommended the use of resampling methods, like the bootstrap method, to calculate the confidence interval, which provides more robust results for inference than does p value. In this review a discussion is made about the use of p values through hypothesis testing and its alternatives using resampling methods to develop confidence intervals of the tested statistic or effect measure.