A Bayesian decision theoretic model of sequential experimentation with delayed response

作者:Chick Stephen*; Forster Martin; Pertile Paolo
来源:Journal of the Royal Statistical Society - Series B: Statistical Methodology , 2017, 79(5): 1439-1462.
DOI:10.1111/rssb.12222

摘要

We propose a Bayesian decision theoretic model of a fully sequential experiment in which the real-valued primary end point is observed with delay. The goal is to identify the sequential experiment which maximizes the expected benefits of technology adoption decisions, minus sampling costs. The solution yields a unified policy defining the optimal do not experiment'-fixed sample size experiment'-sequential experiment' regions and optimal stopping boundaries for sequential sampling, as a function of the prior mean benefit and the size of the delay. We apply the model to the field of medical statistics, using data from published clinical trials.

  • 出版日期2017-11
  • 单位INSEAD