plot_efficiency_frontier: Plot efficiency frontier

In packDAMipd: Decision Analysis Modelling Package with Parameters Estimation Ability from Individual Patient Level Data

Description

Plot efficiency frontier

Usage

plot_efficiency_frontier(results_calculate_icer_nmb, threshold)

Arguments

results_calculate_icer_nmb	results from cea (from calculate_icer_nmb method)
threshold	threshold value

Value

plot 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) results_cea <- calculate_icer_nmb(list_markov, 20000, comparator = "control") plot_efficiency_frontier(results_cea, c(1000, 2000))

packDAMipd documentation built on March 3, 2021, 5:07 p.m.