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Bayesian Designs for Binomial Experiments

  • Conference paper
Foundations of Statistical Inference

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

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Abstract

Calculating the size of the sample required for an experiment is of paramount importance in statistical theory. We describe a new methodology for calculating the optimal sample size when a hypothesis test between two or more binomial proportions takes place. The posterior risk is computed and should not exceed a pre-specified level. A second constraint examines the likelihood of the unknown data not satisfying the bound on the risk.

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References

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Author information

Authors and Affiliations

  1. Department of Statistics and Actuarial Science, University of the Aegean, Samos, Greece

    Athanassios Katsis

  2. Statistical Engineering Division, National Institute of Standards and Technology, Gaithersburg, USA

    Blaza Toman

Authors
  1. Athanassios Katsis
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  2. Blaza Toman
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Editor information

Editors and Affiliations

  1. Department of Statistics, Hebrew University, Jerusalem, 91905, Israel

    Yoel Haitovsky  & Yaacov Ritov  & 

  2. Department of Mathematical Stochastics, University of Freiburg, Eckerstraße 1, Freiburg, 79104, Germany

    Hans Rudolf Lerche

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© 2003 Springer-Verlag Berlin Heidelberg

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Katsis, A., Toman, B. (2003). Bayesian Designs for Binomial Experiments. In: Haitovsky, Y., Ritov, Y., Lerche, H.R. (eds) Foundations of Statistical Inference. Contributions to Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57410-8_8

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  • DOI: https://doi.org/10.1007/978-3-642-57410-8_8

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-0047-0

  • Online ISBN: 978-3-642-57410-8

  • eBook Packages: Springer Book Archive

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