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Article Dans Une Revue Electronic Journal of Applied Statistical Analysis Année : 2020

Bayesian prediction modeling for two-stage experimental trials for Poisson or Gamma distributed data

Résumé

We consider Bayesian prediction modeling to evaluate a satisfaction index after a first phase of experiment in order to decide to stop or continue at the second stage. We apply this method to Poisson and Gamma distributed outcomes in many fields such as reliability or survival analysis for early termination due to either futility or efficacy. We look at two kinds of decisions making: an hybrid Bayesian-frequentist or a full Bayesian approach.
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Dates et versions

hal-04113478 , version 1 (01-06-2023)

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Citer

Pierre Druilhet, Houda Bourezaz, Hayet Merabet. Bayesian prediction modeling for two-stage experimental trials for Poisson or Gamma distributed data. Electronic Journal of Applied Statistical Analysis, 2020, 13 (1), pp.268-283. ⟨10.1285/i20705948v13n1p268⟩. ⟨hal-04113478⟩

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