Statistical evidence and sample size determination for Bayesian hypothesis testing

2004 ◽  
Vol 124 (1) ◽  
pp. 121-144 ◽  
Author(s):  
Fulvio De Santis
2017 ◽  
Author(s):  
Marian Grendar ◽  
George G Judge

A measure of statistical evidence should permit the sample size determination so that the probability M of obtaining (strong) misleading evidence can be held as low as desired. On this desideratum the p-value fails completely, as it leads either to an arbitrary sample size if M >= 0.01 or no sample size at all, if M < 0.01. Unlike the p-value, the ratio of likelihoods, the ratio of posteriors, as well as the Bayes Factor, permit controlling the probability of misleading evidence by the sample size.


2017 ◽  
Author(s):  
Marian Grendar ◽  
George G Judge

A measure of statistical evidence should permit the sample size determination so that the probability M of obtaining (strong) misleading evidence can be held as low as desired. On this desideratum the p-value fails completely, as it leads either to an arbitrary sample size if M >= 0.01 or no sample size at all, if M < 0.01. Unlike the p-value, the ratio of likelihoods, the ratio of posteriors, as well as the Bayes Factor, permit controlling the probability of misleading evidence by the sample size.


2009 ◽  
Vol 6 (2) ◽  
pp. 133-146 ◽  
Author(s):  
Dulal K. Bhaumik ◽  
Anindya Roy ◽  
Nicole A. Lazar ◽  
Kush Kapur ◽  
Subhash Aryal ◽  
...  

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