Model Parameter Estimation and Uncertainty Analysis
Harvard University · Yale University · +3 more institutions
Abstract
A model's purpose is to inform medical decisions and health care resource allocation. Modelers employ quantitative methods to structure the clinical, epidemiological, and economic evidence base and gain qualitative insight to assist decision makers in making better decisions. From a policy perspective, the value of a model-based analysis lies not simply in its ability to generate a precise point estimate for a specific outcome but also in the systematic examination and responsible reporting of uncertainty surrounding this outcome and the ultimate decision being addressed. Different concepts relating to uncertainty in decision modeling are explored. Stochastic (first-order) uncertainty is distinguished from…
Citation impact
- FWCI
- 150.33
- Percentile
- 100%
- References
- 32
Authors
6- ABAndrew BriggsCorresponding
Harvard University, Yale University, University of York, The University of Adelaide, University of Glasgow
- MCMilton C. Weinstein
Harvard University, Yale University, University of York, The University of Adelaide, University of Glasgow
- EFElisabeth Fenwick
Harvard University, Yale University, University of York, The University of Adelaide, University of Glasgow
- JKJonathan Karnon
Harvard University, Yale University, University of York, The University of Adelaide, University of Glasgow
- MSMark Sculpher
Harvard University, Yale University, University of York, The University of Adelaide, University of Glasgow
Topics & keywords
- Sensitivity analysis
- Uncertainty analysis
- Probabilistic logic
- Point estimation
- Decision analysis
- Computer science
- Uncertainty quantification
- Value of information