Resources Repository
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Resource PackPublication, Teaching Resource 2018Resource Pack: Model Calibration and Validation
This resource pack, curated by the Center for Health Decision Science, provides broad exposure to …
This resource pack, curated by the Center for Health Decision Science, provides broad exposure to empirical calibration and validation methods for mathematical models used in health decision analysis. Included are a selection of overviews, guidelines, tutorials, and applications. Given the complexity of diseases and variation in data quality, there are invariably a number of parameters that are unobserved or cannot be estimated directly but can be inferred through the process of model calibration. Model calibration…
Calibration/Validation | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation | Dynamic Simulation | Health/Medicine -
Tutorial/PrimerPublication, Teaching Resource 2017Bayesian Methods for Calibrating Health Policy Models: A Tutorial
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical …
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical basis for Bayesian calibration approaches as well as pragmatic considerations that arise in the tasks of creating calibration targets, estimating the posterior distribution, and obtaining results to inform the policy decision. These considerations, as well as the specific steps for implementing the calibration, are described in the context of an extended worked example about the policy choice to provide (or…
Calibration/Validation | Infectious Diseases | Health/Medicine -
Tutorial/PrimerPublication, Teaching Resource 2015Calibration of Complex Models through Bayesian Evidence Synthesis: A Tutorial
This tutorial demonstrates how to implement a Bayesian synthesis of diverse sources of evidence to …
This tutorial demonstrates how to implement a Bayesian synthesis of diverse sources of evidence to calibrate the parameters of a complex model. To illustrate these methods, the authors demonstrate how a previously developed Markov model for the progression of human papillomavirus (HPV-16) infection was rebuilt in a Bayesian framework. Transition probabilities between states of disease severity are inferred indirectly from cross-sectional observations of prevalence of HPV-16 and HPV-16–related disease by age, cervical cancer incidence, and…
Calibration/Validation | Infectious Diseases