Resources Repository
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GuidelinesPublication 2012Modeling Good Research Practices - Overview: A Report of the ISPOR-SMDM Modeling Task Force-1
This paper provides an overview of the work of the joint Task Force between the …
This paper provides an overview of the work of the joint Task Force between the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), provides the overarching recommendations, and discusses future work that is needed. The audience for these papers includes anyone who build models, stakeholders who utilize their results, and those concerned with the use of models to support decision making. This article is part 1 of…
State-Transition | Value of Information | Health/Medicine | Costing Methods | Health Outcomes | Mathematical Models | Dynamic Transmission | Microsimulation | Calibration/Validation | Dynamic Simulation | Decision Analysis | Infectious Diseases -
GuidelinesPublication 2012State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Task Force-3
State-transition modeling includes both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) …
State-transition modeling includes both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. These models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. Recommendations are made on choice of model type (cohort vs. individual-level model), model…
State-Transition | Health/Medicine | Mathematical Models | Microsimulation -
GuidelinesPublication 2012Model Parameter Estimation and Uncertainty Analysis: A Report of the ISPOR-SMDM Modeling Task Force-6
This paper discusses methods for the reporting of uncertainty, both in terms of deterministic sensitivity …
This paper discusses methods for the reporting of uncertainty, both in terms of deterministic sensitivity analysis techniques and probabilistic methods. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty. The article describes the process of estimating model inputs, whether these are point estimates or distributions. It also explores the link between parameter uncertainty, decision uncertainty, and value-of-information analysis.…
Value of Information | Health/Medicine | Mathematical Models | Calibration/Validation