report_sensitivity_analysis {packDAMipd}

Function to report deterministic sensitivity analysis

Description

Function to report deterministic sensitivity analysis

Usage

report_sensitivity_analysis(
  result_dsa_control,
  result_dsa_treat = NULL,
  threshold = NULL,
  comparator = NULL
)

Arguments

result_dsa_control

result from deterministic sensitivity analysis for first or control model

result_dsa_treat

result from deterministic sensitivity analysis for the comparative Markov model

threshold

threshold value of WTP

comparator

the strategy to be compared with

Value

report in the form of a table

Examples

param_list <- define_parameters(
cost_zido = 2278, cost_direct_med_A = 1701,
cost_comm_care_A = 1055, cost_direct_med_B = 1774,
cost_comm_care_B = 1278,
cost_direct_med_C = 6948, cost_comm_care_C = 2059,
tpAtoA = 1251 / (1251 + 483),
tpAtoB = 350 / (350 + 1384), tpAtoC = 116 / (116 + 1618),
tpAtoD = 17 / (17 + 1717),
tpBtoB = 731 / (731 + 527), tpBtoC = 512 / (512 + 746),
tpBtoD = 15 / (15 + 1243),
tpCtoC = 1312 / (1312 + 437), tpCtoD = 437 / (437 + 1312),
tpDtoD = 1,
cost_health_A = "cost_direct_med_A +  cost_comm_care_A",
cost_health_B = "cost_direct_med_B +  cost_comm_care_B",
cost_health_C = "cost_direct_med_C +  cost_comm_care_C",
cost_drug = "cost_zido")
low_values <- define_parameters(cost_direct_med_B = 177.4,
cost_comm_care_C = 205.9)
upp_values <- define_parameters(cost_direct_med_B = 17740,
cost_comm_care_C = 20590)
A <- health_state("A", cost = "cost_health_A +  cost_drug ", utility = 1)
B <- health_state("B", cost = "cost_health_B + cost_drug", utility = 1)
C <- health_state("C", cost = "cost_health_C + cost_drug", utility = 1)
D <- health_state("D", cost = 0, utility = 0)
tmat <- rbind(c(1, 2, 3, 4), c(NA, 5, 6, 7), c(NA, NA, 8, 9),
c(NA, NA, NA, 10))
colnames(tmat) <- rownames(tmat) <- c("A", "B", "C", "D")
tm <- populate_transition_matrix(4, tmat, c("tpAtoA", "tpAtoB", "tpAtoC",
"tpAtoD","tpBtoB", "tpBtoC", "tpBtoD", "tpCtoC", "tpCtoD", "tpDtoD"),
colnames(tmat))
health_states <- combine_state(A, B, C, D)
mono_strategy <- strategy(tm, health_states, "mono")
mono_markov <- markov_model(mono_strategy, 20, c(1, 0, 0, 0),
discount = c(0.06, 0), param_list)
param_table <- define_parameters_sens_anal(param_list, low_values,
upp_values)
result <- do_sensitivity_analysis(mono_markov, param_table)
 reporting <- report_sensitivity_analysis(result)