calculate_icer_nmb {packDAMipd}

Estimation of ICER and NMB

Description

Estimation of ICER and NMB

Usage

calculate_icer_nmb(list_markov, threshold, comparator = NULL)

Arguments

list_markov

list of Markov model objects with their Markov trace, cost matrix and utility matrix

threshold

threshold value of WTP

comparator

the strategy to be compared with

Value

ICER and NMB for all the strategies compared to comparator

Examples

well <- health_state("well", cost = 0, utility = 1)
disabled <- health_state("disabled", cost = 100, utility = 1)
dead <- health_state("dead", cost = 0, utility = 0)
tmat <- rbind(c(1, 2, 3), c(NA, 4, 5), c(NA, NA, 6))
colnames(tmat) <- rownames(tmat) <- c("well", "disabled", "dead")
tm <- populate_transition_matrix(3, tmat, c(0.6, 0.2, 0.2, 0.6, 0.4, 1),
colnames(tmat))
health_states <- combine_state(well, disabled, dead)
this.strategy <- strategy(tm, health_states, "control")
this_markov <- markov_model(this.strategy, 24, c(1000, 0, 0), c(0,0))
well <- health_state("well", cost = 0, utility = 1)
disabled <- health_state("disabled", cost = 10, utility = 0.5)
dead <- health_state("dead", cost = 0, utility = 0)
tmat <- rbind(c(1, 2, 3), c(NA, 4, 5), c(NA, NA, 6))
colnames(tmat) <- rownames(tmat) <- c("well", "disabled", "dead")
tm <- populate_transition_matrix(3, tmat, c(0.4, 0.4, 0.2, 0.6, 0.4, 1),
colnames(tmat))
health_states <- combine_state(well, disabled, dead)
this.strategy <- strategy(tm, health_states, "intervention")
sec_markov <- markov_model(this.strategy, 24, c(1000, 0, 0), c(0,0))
list_markov <- combine_markov(this_markov, sec_markov)
calculate_icer_nmb(list_markov, 20000, comparator = "control")