Process / pipelineSimulation / optimization

Stochastic Markov Model — Probabilistic State-Transition Simulation with Uncertainty Propagation

A Stochastic Markov Model is a simulation technique that represents a system as a set of mutually exclusive health or decision states, moves a cohort (or individual agents) through those states using probabilistically sampled transition parameters, and aggregates outcomes across thousands of Monte Carlo iterations to produce full probability distributions over costs, outcomes, or rankings rather than single point estimates.

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Sources

  1. Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: A practical guide. Medical Decision Making, 13(4), 322–338. DOI: 10.1177/0272989X9301300409
  2. Briggs, A., Sculpher, M., & Claxton, K. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press. ISBN: 9780198526629

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Referenced by

ScholarGateStochastic Markov Model (Stochastic Markov Model — Probabilistic State-Transition Simulation with Uncertainty Propagation). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/stochastic-markov-model