This paper will present methods for assessing and reporting parameter estimation (including calibration) and uncertainty in models. In addition to uni-or muli-variate sensitivity analyses, the correlation of input variables will be addressed. In this paper, the use of Bayesian approaches to integrate prior knowledge will be discussed.

Working Group Chair (Lead author):
Andrew Briggs DPhil, Lindsay Chair in Health Policy & Economic Evaluation, Public Health & Health Policy, University of Glasgow, Glasgow, Scotland UK

Working Group Members (Co-authors):
Elizabeth Fenwick PhD, MSc, Lecturer in Health Economics, University of Glasgow, Glasgow, Scotland, United Kingdom
Jonathon Karnon PhD, Professor in Health Economics, University of Adelaide, Adelaide, South Australia
A. David Paltiel PhD, Professor and Acting Division Head, Yale University, Yale School of Public Health, New Haven, CT, USA
Mark Sculpher PhD, MSc, Professor, University of York, Heslington, York, England, United Kingdom
Milton Weinstein PhD, Professor Health Policy & Management, Harvard School of Public Health, Boston, MA USA

For more information on the ISPOR-SMDM Modeling Good Research Practices Task Force (Leadership, Goal, Background / Overview, Timeline) please refer to the following page: http://www.ispor.org/TaskForces/GRPModelingTf.asp

For further recommendations on modeling good research practices, please refer to the following reports:

• Modeling Good Research Practices: Overview, Issues, and Preferred Practices
• Conceptual Modeling and Data Source and Preparation Good Research Practices
• State-Transition Modeling Good Research Practices
• Discrete Event Simulation Modeling Good Research Practices
• Dynamic Transmission Modeling Good Research Practices
• Model Parameter Estimation and Uncertainty Good Research Practices
• Model Transparency and Validation Good Research Practices

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ISPOR-SMDM Modeling Good Research Practices
Joint Task Force