Post-data Power Estimation
- 2002-02-25 (Mon.), 10:30 AM
- Recreation Hall, 2F, Institute of Statistical Science
- Prof. Chen-Hai Andy Tsao
- Department of Applied Mathematics, National Dong Hwa University
Abstract
Under a robust Bayesian framework, we study the properties of observed power and p-values as post-data evidences in hypotheses testing problems. For the one-sided hypotheses testing problem for the normal mean, both measures correspond to MLE for functions of unknown parameters. We show that for a reasonable families of priors, MLE tends to be extreme in some sense. Implications on the controversies of ir/reconcilability of p-values in Berger and Delampady (1987) and Casella and Berger (1987) will also be addressed.
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