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Sambucini, V. (2017) Bayesian vs Frequentist Power Functions to Determine the Optimal Sample Size: Testing One Sample Binomial Proportion Using Exact Methods. In: Tejedor, J.P., Ed., Bayesian Inference, InTech, 77-97.
https://doi.org/10.5772/intechopen.70168

has been cited by the following article:

• TITLE: On the Interpretation and the Choice of the Hyperparameters of a Beta Prior Distribution

  AUTHORS: Valeria Sambucini

  KEYWORDS: Beta Prior Distributions, Binary Data, Elicitation, Extra Data, Prior Sample Size

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.15 No.9, September 3, 2025

  ABSTRACT: Binary outcomes are frequently encountered in a variety of fields and contexts and the Bayesian approach is widely used to analyze this type of data. Under this framework, a beta prior distribution for the probability of success is typically used. We clarify why in the statistical literature one can find two slightly different interpretations of the prior hyperparameters as extra data. The two interpretations can be exploited to elicit informative beta prior densities by specifying a measure of central tendency and a suitable value for the prior sample size. We developed a Shiny App in R that provides a user-friendly interface to implement the elicitation procedures.