Microsimulation Model Calibration with Approximate Bayesian Computation in R: A Tutorial.

ABSTRACT: Mathematical health policy models, including microsimulation models (MSMs), are widely used to simulate complex processes and predict outcomes consistent with available data. Calibration is a method to estimate parameter values such that model predictions are similar to observed outcomes of interest. Bayesian calibration methods are popular among the available calibration techniques, given their strong theoretical basis and flexibility to incorporate prior beliefs and draw values from the posterior distribution of model parameters and hence the ability to characterize and evaluate parameter uncertainty in the model outcomes. Approximate Bayesian computation (ABC) is an approach to calibrate complex models in which the likelihood is intractable, focusing on measuring the difference between

SUBMITTER: Shewmaker P 

PROVIDER: S-EPMC9198004 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature