A Bayesian Approach to Sensitivity Analysis
Abstract
Sensitivity 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.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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