Optimizing Monte Carlo Sampling in Health-Economic Modeling: Underlying Concepts and Parameter Definitions

Abstract

The research presented by Yaesoubi is of great interest for the subject of Monte Carlo (MC) simulations in health-economic modeling. Indeed, the justification for determining N (2nd-order MC, parameter sampling) and P (1st-order MC, same individuals) is very rarely, if at all absent from health-economic studies. The aim of this response is to extend the discussion by looking at underlying concepts such as variability versus uncertainty, the limits of (pseudo)-random number generators, calculation constraints, and alternative ways of determining N and P to optimize the number of simulations.

 

Authors

Stéphane Roze

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