Calibration of a microsimulation model (MSM) is a challenging but crucial step for the
development of a valid model. Numerous calibration methods for MSMs have been …

The Microsimulation Lung Cancer (MILC) model was developed to simulate individual
trajectories and predict outcomes of lung cancer for populations. The model describes the …

Mathematical health policy models, including microsimulation models (MSMs), are widely
used to simulate complex processes and predict outcomes consistent with available data …

Objectives: Calibrating a disease simulation model's outputs to existing clinical data is vital
to generate confidence in the model's predictive ability. Calibration involves two challenges …

Microsimulation models (MSMs) are used to inform policy by predicting population-level
outcomes under different scenarios. MSMs simulate individual-level event histories that …

Microsimulation models that describe disease processes synthesize information from
multiple sources and can be used to estimate the effects of screening and treatment on …

Background Microsimulation models are mathematical models that simulate event histories
for individual members of a population. They are useful for policy decisions because they …

Background. Microsimulation models have been extensively used in the field of cancer
modeling. However, there is substantial uncertainty regarding estimates from these models …

Background. Calibration (estimation of model parameters) compares model outcomes with
observed outcomes and explores possible model parameter values to identify the set of …

Background. Microsimulation models (MSMs) for health outcomes simulate individual event
histories associated with key components of a disease process; these simulated life histories …