Vertaile menetelmiä
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| Deterministinen Markov-malli× | Herkkyysanalyysi× | |
|---|---|---|
| Tieteenala≠ | Simulointi | Päätöksenteko |
| Menetelmäperhe≠ | Process / pipeline | MCDM |
| Syntyvuosi≠ | 1993 | 2004 |
| Kehittäjä≠ | Sonnenberg, F. A. & Beck, J. R. | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. |
| Tyyppi≠ | Cohort state-transition model with fixed transition probabilities | Robustness wrapper — parameter / weight perturbation sensitivity indices |
| Alkuperäislähde≠ | Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Medical Decision Making, 13(4), 322–338. DOI ↗ | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. (2004). Sensitivity Analysis in Practice. Wiley, Chichester DOI ↗ |
| Rinnakkaisnimet≠ | DMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model | — |
| Liittyvät≠ | 5 | 0 |
| Tiivistelmä≠ | 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. | 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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