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Markov Models, Cycles
The Markov model provides a means of representing clinical situations in which risk is continuous, probabilities may change over time, or events may occur more than once. Markov models represent clinical events as transitions between health states, known as Markov states. Several advanced techniques extend the versatility of this modeling method.
Appropriate Use of Rates and Probabilities
Rates versus Probabilities
Because Markov models inherently represent the passage of time, the transition probabilities must reflect a specific time frame. The Markov model shown as a state transition diagram in Figure 1 and as a Markov cycle tree in Figure 2 represents a person in the WELL state becoming either DISABLED or DEAD or a person in the DISABLED state becoming DEAD. Since the events represented in the cycle tree ...
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