Bayesian computations for Value of Information measures using Gaussian processes, INLA and Moment Matching

Published: Jun 28, 2018
Abstract
Value of Information measures quantify the economic benefit of obtaining additional information about the underlying model parameters of a health economic model. Theoretically, these measures can be used to understand the impact of model uncertainty on health economic decision making. Specifically, the Expected Value of Partial Perfect Information (EVPPI) can be used to determine which model parameters are driving decision uncertainty. This is...
Paper Details
Title
Bayesian computations for Value of Information measures using Gaussian processes, INLA and Moment Matching
Published Date
Jun 28, 2018
Journal
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