In Brief

Professor of Health Policy Jeremy Goldhaber-Fiebert, PhD, discusses the rationale of using state-transition models, dynamic modeling, discrete event simulation, agent-based modeling, and Markov decision process models. Subsequently, the discussion moves to recent developments in calibration and validation with reflections on Bayesian calibration, meta-models, and accounting for correlation between input parameters.

This video is part of a series developed by Professor of Health Decision Sciences Myriam Hunink, MD, PhD, during an immersion residency with the Media Hub at the Center for Health Decision Science at the Harvard T.H. Chan School of Public Health. The interview was facilitated by Hunink during the Society for Medical Decision Making (SMDM) 46th annual meeting held in Boston, Massachusetts.