Metamodeling for Policy Simulations with Multivariate Outcomes.

Journal: Medical decision making : an international journal of the Society for Medical Decision Making
Published Date: Jun 23, 2022

Abstract

PURPOSE: Metamodels are simplified approximations of more complex models that can be used as surrogates for the original models. Challenges in using metamodels for policy analysis arise when there are multiple correlated outputs of interest. We develop a framework for metamodeling with policy simulations to accommodate multivariate outcomes.

Authors

  • Huaiyang Zhong
    Department of Management Science and Engineering, Stanford University, Stanford, CA, USA.
  • Margaret L Brandeau
    Department of Management Science and Engineering, Stanford University, Stanford, CA, USA.
  • Golnaz Eftekhari Yazdi
    Section of Infectious Diseases, Department of Medicine, Boston Medical Center, Boston, MA, USA.
  • Jianing Wang
    Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA. Electronic address: jianing.wang@vanderbilt.edu.
  • Shayla Nolen
    Section of Infectious Diseases, Department of Medicine, Boston Medical Center, Boston, MA, USA.
  • Liesl Hagan
  • William W Thompson
    Division of Viral Hepatitis, Center for Disease Control and Prevention, Atlanta, GA, USA.
  • Sabrina A Assoumou
    Section of Infectious Diseases, Department of Medicine, Boston Medical Center, Boston, MA, USA.
  • Benjamin P Linas
    Department of Medicine, Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.
  • Joshua A Salomon
    Center for Health Policy and Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.

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