Martin Forster, Department of Economics and Related Studies,
University of York, UK
http://www.york.ac.uk/economics/our-people/staff-profiles/martin-forster/
er/ Distance Learning Programmes in Health Economics
http://www.york.ac.uk/economics/postgrad/distance_learning/
Abstract
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 maximises 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 a published trial investigating the clinical- and cost-effectiveness of drug-eluting stents versus bare metal stents.
Keywords: Bayesian inference; Clinical trials; Delayed observations;
Health economics; Sequential experimentation
Working paper available at: http://econpapers.repec.org/paper/yoryorken/15_2f09.htm
Contact person
Rosa Bernardini Papalia