summary_plot_psa {packDAMipd} | R Documentation |
Function to summarise and plot probabilistic sensitivity analysis
Description
Function to summarise and plot probabilistic sensitivity analysis
Usage
summary_plot_psa(
result_psa_params_control,
result_psa_params_treat = NULL,
threshold = NULL,
comparator = NULL
)
Arguments
result_psa_params_control |
result from probabilistic sensitivity analysis for first or control model |
result_psa_params_treat |
result from probabilistic sensitivity analysis for the comparative Markov model |
threshold |
threshold value of WTP |
comparator |
the strategy to be compared with |
Value
plot of sensitivity analysis
Examples
param_list <- define_parameters(
cost_direct_med_A = 1701,
cost_direct_med_B = 1774, tpAtoA = 0.2,
tpAtoB = 0.5, tpAtoC = 0.3,
tpBtoB = 0.3, tpBtoC = 0.7,
tpCtoC = 1,cost_health_A = "cost_direct_med_A",
cost_health_B = "cost_direct_med_B")
sample_list <- define_parameters(cost_direct_med_A = "gamma(mean = 1701,
sd = sqrt(1701))")
A <- health_state("A", cost = "cost_health_A ", utility = 1)
B <- health_state("B", cost = "cost_health_B", utility = 1)
C <- health_state("C", cost = 0, utility = 0, absorb = "TRUE")
tmat <- rbind(c(1, 2, 3), c(NA, 4, 5), c(NA, NA, 6))
colnames(tmat) <- rownames(tmat) <- c("A", "B", "C")
tm <- populate_transition_matrix(3, tmat, c(
"tpAtoA", "tpAtoB", "tpAtoC", "tpBtoB", "tpBtoC", "tpCtoC"),
colnames(tmat))
health_states <- combine_state(A, B, C)
mono_strategy <- strategy(tm, health_states, "mono")
mono_markov <- markov_model(mono_strategy, 20, initial_state =c(1,0,0),
discount = c(0.06, 0),param_list)
param_table <- define_parameters_psa(param_list, sample_list)
result <- do_psa(mono_markov, param_table, 3)
result_plot <- summary_plot_psa(result, NULL, NULL, NULL)
param_list_comb <- define_parameters(
cost_direct_med_A = 1800, cost_direct_med_B = 1774, tpAtoA = 0.6,
tpAtoB = 0.1, tpAtoC = 0.3,tpBtoB = 0.3, tpBtoC = 0.7,tpCtoC = 1,
cost_health_A = "cost_direct_med_A",cost_health_B = "cost_direct_med_B")
comb_strategy <- strategy(tm, health_states, "comb")
comb_markov <- markov_model(comb_strategy, 20, c(1, 0, 0),
discount = c(0.06, 0), param_list)
param_table_comb <- define_parameters_psa(param_list_comb, sample_list)
result_comb <- do_psa(comb_markov, param_table_comb, 3)
summary_plot_psa(result, result_comb, 2000, "mono")
[Package packDAMipd version 1.1.0 Index]