TY - JOUR
T1 - Systematic deviation in mean of log bayes factor
T2 - Implication and application
AU - Midya, Vishal
AU - Liao, Jiangang
N1 - Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.
PY - 2023
Y1 - 2023
N2 - This article works with an expression of the mean of log Bayes Factor to elucidate its dependence on specified priors. Such explication answers some basic questions about interpreting Bayes Factor as evidence against a null or an alternative hypothesis. It also provides a powerful tool to study the behavior of the Bayes Factor under various underlying distributions that may generate the data. A new concept, the neutral distribution, is proposed to evaluate performances of Bayesian methods across sample space. It quantifies the deviation in a log Bayes Factor in favoring the null hypothesis when the data is generated under an alternative hypothesis. Eventually this method provides a tool to obtain an estimate of the sample size needed to stand a reasonable chance in obtaining compelling evidence. An application of this concept is presented in the context of Bayesian Two-sample t-tests.
AB - This article works with an expression of the mean of log Bayes Factor to elucidate its dependence on specified priors. Such explication answers some basic questions about interpreting Bayes Factor as evidence against a null or an alternative hypothesis. It also provides a powerful tool to study the behavior of the Bayes Factor under various underlying distributions that may generate the data. A new concept, the neutral distribution, is proposed to evaluate performances of Bayesian methods across sample space. It quantifies the deviation in a log Bayes Factor in favoring the null hypothesis when the data is generated under an alternative hypothesis. Eventually this method provides a tool to obtain an estimate of the sample size needed to stand a reasonable chance in obtaining compelling evidence. An application of this concept is presented in the context of Bayesian Two-sample t-tests.
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U2 - 10.1080/03610926.2021.1970768
DO - 10.1080/03610926.2021.1970768
M3 - Article
AN - SCOPUS:85114268459
SN - 0361-0926
VL - 52
SP - 3209
EP - 3218
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 10
ER -