Estimating the expected value of partial perfect information: a review of methods.
Identifieur interne : 002197 ( Main/Exploration ); précédent : 002196; suivant : 002198Estimating the expected value of partial perfect information: a review of methods.
Auteurs : Doug Coyle [Canada] ; Jeremy OakleySource :
- The European journal of health economics : HEPAC : health economics in prevention and care [ 1618-7598 ] ; 2008.
English descriptors
- KwdEn :
- MESH :
- economics : Parkinson Disease.
- methods : Statistics as Topic.
- Canada, Decision Making, Health Care Costs, Humans, Markov Chains, Models, Economic, Monte Carlo Method, Ontario, Pilot Projects, United Kingdom.
Abstract
Value of information analysis provides a framework for the analysis of uncertainty within economic analysis by focussing on the value of obtaining further information to reduce uncertainty. The mathematical definition of the expected value of perfect information (EVPI) is fixed, though there are different methods in the literature for its estimation. In this paper these methods are explored and compared.
DOI: 10.1007/s10198-007-0069-y
PubMed: 17638032
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Value of information analysis provides a framework for the analysis of uncertainty within economic analysis by focussing on the value of obtaining further information to reduce uncertainty. The mathematical definition of the expected value of perfect information (EVPI) is fixed, though there are different methods in the literature for its estimation. In this paper these methods are explored and compared.</div>
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