Resources Repository
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Tutorial/PrimerPublication, Teaching Resource 2024Tutorial: Building Decision Trees
This tutorial illustrates the basic steps needed to develop decision trees in Amua using a …
This tutorial illustrates the basic steps needed to develop decision trees in Amua using a disease screening example. It details the process of how to build the structure of a decision tree, parameterize the model with probabilities and relevant outcomes (i.e., life expectancy), evaluate three alternative screening strategies in a baseline scenario, and perform one-way sensitivity analyses to assess the robustness of the results to different parameter values. Amua, the Swahili word meaning “decide”/“solve”, is…
Probability/Bayes | Clinical Care | Mathematical Models | Decision Analysis | Health/Medicine | Graduate | Doctoral | Professional -
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