Cohort simulation of a state-transition model
m_(t+1) = m_t P_t; Y = sum_(t=0)^T w_t delta_t m_t r
Maps a starting distribution of the cohort across health states, the transition matrix for each cycle, the reward per cycle in each state, the discount factors and a within-cycle counting rule to the expected total cost, life years or QALYs per person. The cycle-by-cycle trace m_(t+1) = m_t P_t is the cohort state update of the Markov Model page, which gives it in its time-homogeneous form s_(t+1) = s_t P (HE-FM-MM-001); here P_t may vary from cycle to cycle, and the update is not restated. Because each state is homogeneous, the proportion in a state equals the probability that one member of the cohort is in it, so the accumulated rewards are expected values per person. Two existing formulae check a run: the area under an exponential survival curve over one interval (HE-FM-BTH-001) gives a continuous-time benchmark for counting rules, and the fundamental matrix (HE-FM-ABS-001) gives the totals of a run to absorption counted at the start of each cycle.
Expected outcome per person from a cohort simulation trace with counting weights and discounting
Y = sum_(t=0)^T [w_t * delta_t * m_t * r]