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


We consider Bayesian prediction modelling 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.

DOI Code: 10.1285/i20705948v13n1p268

Keywords: Bayesian predictive distribution; satisfaction indices; two-stage sequential analysis; experimental trials; Poison and Gamma outcomes.


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