השוואת שיטות

	מודל מרקוב דטרמיניסטי – ניתוח מעברי מצב של עוקבה עם פרמטרים קבועים	מודל מרקוב
תחום	סימולציה	סימולציה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1993	1906
הוגה השיטה	Sonnenberg, F. A. & Beck, J. R.	Andrei Markov
סוג	Cohort state-transition model with fixed transition probabilities	Probabilistic state-transition model
מקור מכונן	Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Medical Decision Making, 13(4), 322–338.	Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963
כינויים	DMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model	Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process
קשורות	5	5
תקציר	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.