方法对比
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| 稳健微观模拟× | 随机微观模拟× | |
|---|---|---|
| 领域 | 仿真 | 仿真 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s | 1957 |
| 提出者≠ | Briggs, A. H.; O'Brien, B. J. and others in health technology assessment literature | Guy H. Orcutt |
| 类型≠ | Simulation with systematic robustness testing | Stochastic individual-level simulation |
| 开创性文献≠ | O'Brien, B. J., & Briggs, A. H. (2002). Analysis of uncertainty in health care cost-effectiveness studies: an introduction to statistical issues and methods. Statistical Methods in Medical Research, 11(6), 455-468. DOI ↗ | Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123. DOI ↗ |
| 别名 | Robust Micro-Simulation, Uncertainty-Robust Microsimulation, Probabilistic Microsimulation, Sensitivity-Enhanced Microsimulation | Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM |
| 相关≠ | 5 | 6 |
| 摘要≠ | Robust Microsimulation combines individual-level (micro) simulation with systematic uncertainty analysis — typically probabilistic sensitivity analysis — to generate outputs that are robust to parameter uncertainty, model structure assumptions, and input variability. It is widely used in health technology assessment, public policy, and social science to produce credible, decision-relevant predictions. | Stochastic Microsimulation tracks a large population of individual units — people, households, or firms — through time by applying random draws from empirically estimated probability distributions at each transition event. Unlike deterministic counterparts, every state change is decided by chance, preserving realistic heterogeneity and allowing rigorous uncertainty quantification across multiple simulation runs. |
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