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Bayesian P Values

  • Lemuel A. Moyé

Abstract

There are no substitutes for p values when a statistical interrogation must lead to a decision. It will therefore come as no surprise when I say that their use requires careful, deliberate thought. Even in the simplest of experiments, investigators must think critically and prospectively about the degree of community protection they wish to provide as they determine the type I and type II errors. As I pointed out in chapters 7 and 8, the application of p values to experiments in health care is even more complicated when these experiments have more than two treatment arms and multiple endpoints. In all cases, the experiment must be executed concordantly, according to the protocol, so that the resulting p values are interpretable. These endeavors are not to be undertaken lightly.

Keywords

Posterior Distribution Loss Function Prior Distribution Bayesian Approach Asthma Prevalence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Berger, J.O., (1980) Statistical Decision Theory. Foundations, Concepts and Methods. Springer-Verlag, New York.Google Scholar
  2. 2.
    Lindley, D.V., (1976) “Inference for a Bernoulli process (a Bayesian view)”, The American Statistician 30: 112–118.Google Scholar
  3. 3.
    Pratt, J.W., (1962) “Discussion of A. Birnbaum’s On the foundations of statistical inference,” Journal of the American Statistical Association 57: 269–326.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Lemuel A. Moyé
    • 1
  1. 1.School of Public HealthUniversity of TexasHoustonUSA

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