packDAMipd (version 1.1.0)

calculate_icer_nmb: Estimation of ICER and NMB

Description

Estimation of ICER and NMB

Usage

calculate_icer_nmb(list_markov, threshold, comparator = NULL)

Value

ICER and NMB for all the strategies compared to comparator

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

Examples

# \donttest{
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")
# }