Saved in:
Bibliographic Details
Main Authors: Al-Labadi, Luai, Alzaatreh, Ayman, Evans, Michael
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2301.08994
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917598494457856
author Al-Labadi, Luai
Alzaatreh, Ayman
Evans, Michael
author_facet Al-Labadi, Luai
Alzaatreh, Ayman
Evans, Michael
contents Both the Bayes factor and the relative belief ratio satisfy the principle of evidence and so can be seen to be valid measures of statistical evidence. Certainly Bayes factors are regularly employed. The question then is: which of these measures of evidence is more appropriate? It is argued here that there are questions concerning the validity of a current commonly used definition of the Bayes factor based on a mixture prior and, when all is considered, the relative belief ratio has better properties as a measure of evidence. It is further shown that, when a natural restriction on the mixture prior is imposed, the Bayes factor equals the relative belief ratio obtained without using the mixture prior. Even with this restriction, this still leaves open the question of how the strength of evidence is to be measured. It is argued here that the current practice of using the size of the Bayes factor to measure strength is not correct and a solution to this issue is presented. Several general criticisms of these measures of evidence are also discussed and addressed.
format Preprint
id arxiv_https___arxiv_org_abs_2301_08994
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle How to Measure Evidence and Its Strength: Bayes Factors or Relative Belief Ratios?
Al-Labadi, Luai
Alzaatreh, Ayman
Evans, Michael
Statistics Theory
Methodology
Machine Learning
Both the Bayes factor and the relative belief ratio satisfy the principle of evidence and so can be seen to be valid measures of statistical evidence. Certainly Bayes factors are regularly employed. The question then is: which of these measures of evidence is more appropriate? It is argued here that there are questions concerning the validity of a current commonly used definition of the Bayes factor based on a mixture prior and, when all is considered, the relative belief ratio has better properties as a measure of evidence. It is further shown that, when a natural restriction on the mixture prior is imposed, the Bayes factor equals the relative belief ratio obtained without using the mixture prior. Even with this restriction, this still leaves open the question of how the strength of evidence is to be measured. It is argued here that the current practice of using the size of the Bayes factor to measure strength is not correct and a solution to this issue is presented. Several general criticisms of these measures of evidence are also discussed and addressed.
title How to Measure Evidence and Its Strength: Bayes Factors or Relative Belief Ratios?
topic Statistics Theory
Methodology
Machine Learning
url https://arxiv.org/abs/2301.08994