Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models

Abstract

Background: Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Methods: Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distri..