Salīdzināt metodes

	Robust Microsimulation	Stohastiskā mikrosimulācija
Nozare	Simulācija	Simulācija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1990s–2000s	1957
Autors	Briggs, A. H.; O'Brien, B. J. and others in health technology assessment literature	Guy H. Orcutt
Tips	Simulation with systematic robustness testing	Stochastic individual-level simulation
Pirmavots	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.	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123.
Citi nosaukumi	Robust Micro-Simulation, Uncertainty-Robust Microsimulation, Probabilistic Microsimulation, Sensitivity-Enhanced Microsimulation	Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM
Saistītās	5	6
Kopsavilkums	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.