Choosing a Metamodel of a Simulation Model for Uncertainty Quantification.
Journal:
Medical decision making : an international journal of the Society for Medical Decision Making
Published Date:
Jun 8, 2021
Abstract
BACKGROUND: Metamodeling may substantially reduce the computational expense of individual-level state transition simulation models (IL-STM) for calibration, uncertainty quantification, and health policy evaluation. However, because of the lack of guidance and readily available computer code, metamodels are still not widely used in health economics and public health. In this study, we provide guidance on how to choose a metamodel for uncertainty quantification.