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| Deterministisches Markov-Modell× | Markov-Modell× | |
|---|---|---|
| Fachgebiet | Simulation | Simulation |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1993 | 1906 |
| Urheber≠ | Sonnenberg, F. A. & Beck, J. R. | Andrei Markov |
| Typ≠ | Cohort state-transition model with fixed transition probabilities | Probabilistic state-transition model |
| Wegweisende Quelle≠ | Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Medical Decision Making, 13(4), 322–338. DOI ↗ | Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963 |
| Aliasnamen | DMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model | Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | A 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. | A Markov Model represents a system as a finite set of states and specifies the probability of moving from one state to another at each time step. By capturing only the current state — not the full history — it enables tractable analysis of complex dynamic processes across health economics, engineering reliability, operations research, and social-science modeling. |
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