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Deterministisch Markov-model×Monte Carlo Simulatie×
VakgebiedSimulatieBesluitvorming
FamilieProcess / pipelineMCDM
Jaar van ontstaan19931949
GrondleggerSonnenberg, F. A. & Beck, J. R.Metropolis, N., Ulam, S.
TypeCohort state-transition model with fixed transition probabilitiesRobustness wrapper — Monte Carlo uncertainty propagation
Oorspronkelijke bronSonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Medical Decision Making, 13(4), 322–338. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
AliassenDMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model
Verwant50
SamenvattingA Deterministic Markov Model is a cohort-level state-transition model in which all transition probabilities, state utilities, and costs are assigned single fixed values and the model is solved analytically in a single pass. Widely used in health technology assessment, policy analysis, and operations research, it traces a hypothetical cohort through mutually exclusive health or system states over discrete time cycles, accumulating expected outcomes such as quality-adjusted life years (QALYs) or costs.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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  3. PUBLISHED

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