Blending Bayesian and frequentist methods according to the precision of prior information with applications to hypothesis testing

@article{Bickel2015BlendingBA,
  title={Blending Bayesian and frequentist methods according to the precision of prior information with applications to hypothesis testing},
  author={D. Bickel},
  journal={Statistical Methods & Applications},
  year={2015},
  volume={24},
  pages={523-546}
}
  • D. Bickel
  • Published 2015
  • Mathematics, Computer Science
  • Statistical Methods & Applications
  • The proposed minimax procedure blends strict Bayesian methods with p values and confidence intervals or with default-prior methods. Two applications to hypothesis testing bring some implications to light. First, the blended probability that a point null hypothesis is true is equal to the p value or a lower bound of an unknown posterior probability, whichever is greater. As a result, the p value is reported instead of any posterior probability in the case of complete prior ignorance but is… CONTINUE READING
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