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dc.contributor.authorFelli, James C.
dc.contributor.authorHazen, Gordon B.
dc.date.accessioned2014-12-11T23:39:22Z
dc.date.available2014-12-11T23:39:22Z
dc.date.issued1999
dc.identifier.citationHealth Economics, Volume 8, pp. 263-268, 1999.
dc.identifier.urihttp://hdl.handle.net/10945/44157
dc.description.abstractSensitivity analysis has traditionally been applied to decision models to quantify the stability of a preferred alternative to parametric variation. In the health literature, sensitivity measures have traditionally been based upon distance metrics, payoff variations, and probability measures. We advocate a new approach based on information value and argue that such an approach is better suited to address the decision-maker's real concerns. We provide an example comparing conventional sensitivity analysis to one based on information value. This article is a US government work and is in the public domain in the United States.en_US
dc.publisherHealth Economics Letteren_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.titleA Bayesian Approach to Sensitivity Analysisen_US
dc.typeNewsletteren_US
dc.contributor.corporateDefense Resources Management Institute (DRMI)
dc.subject.authorBayesian decision theoryen_US
dc.subject.authorthe value of informationen_US
dc.subject.authoreconomics of informationen_US
dc.subject.authorstatistical methodsen_US
dc.description.funderThis work was supported by funding from the Decision, Risk and Management Science Program at the National Science Foundation.en_US


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