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| Politikszenario-Monte-Carlo-Simulation× | SENSITIVITY-ANALYSIS× | |
|---|---|---|
| Fachgebiet≠ | Simulation | Entscheidungsfindung |
| Familie≠ | Process / pipeline | MCDM |
| Entstehungsjahr≠ | 1990s–2000s | 2004 |
| Urheber≠ | Developed within health economics and policy modeling communities; foundational work by Briggs, Claxton, and Sculpher | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. |
| Typ≠ | Probabilistic scenario simulation | Robustness wrapper — parameter / weight perturbation sensitivity indices |
| Wegweisende Quelle≠ | Briggs, A. H., Claxton, K., & Sculpher, M. J. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press. ISBN: 9780198526629 | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. (2004). Sensitivity Analysis in Practice. Wiley, Chichester DOI ↗ |
| Aliasnamen≠ | PS-MCS, Policy MC Simulation, Scenario-Based Monte Carlo, Policy Uncertainty Simulation | — |
| Verwandt≠ | 4 | 0 |
| Zusammenfassung≠ | Policy Scenario Monte Carlo Simulation combines pre-defined discrete policy scenarios with probabilistic Monte Carlo sampling to quantify uncertainty in outcomes across each scenario. Rather than evaluating a single stochastic model, analysts define two or more policy alternatives and run thousands of Monte Carlo iterations within each, producing probability distributions of outcomes that support evidence-based policy comparison. | SENSITIVITY-ANALYSIS (Sensitivity Analysis — Systematic assessment of output variation w.r.t. input perturbations) is a ranking multi-criteria decision-making (MCDM) method introduced by Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. in 2004. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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