get_all_parameter_list: Function to estimate the expected value of partial perfect...

In sheejamk/packEVPI: Estimate Expected Value of Perfect Information

Function to estimate the expected value of partial perfect information

Description

Function to estimate the expected value of partial perfect information

Usage

get_all_parameter_list(
  names_params_needed,
  names_params_model,
  params_passed,
  param_file,
  colnames_paramdistr
)

Arguments

names_params_needed	names of needed parameters from param matrix returned
names_params_model	names of parameters in the model
params_passed	parameters passed while running the markov model
param_file	all parameters required to run the model,provided with name of parameter, distribution and parameters that define the probability distribution
colnames_paramdistr	col names where the parameter distribution is defined

Details

this function gets all the parameters except the parameter of interest if they parameter is fixed, just read from file or a distribution, then gets it from a distribution, or if it to be calculated, just give it back as it is

Value

current_parameter_list set of all parameters

Examples

well <- packDAMipd::health_state("well", cost = "cost_well_co", utility = 1)
disabled <- packDAMipd::health_state("disabled", cost = "cost_dis_co",
utility = "utility_dis_co")
dead <- packDAMipd::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 <- packDAMipd::populate_transition_matrix(3, tmat,
c("tp_well_well_co","tp_well_dis_co","tp_well_dead", "tp_dis_dis_co",
"tp_dis_dead", "tp_dead_dead"),colnames(tmat))
health_states <- packDAMipd::combine_state(well, disabled, dead)
this.strategy <- packDAMipd::strategy(tm, health_states, "control")
param_file <- system.file("extdata", "table_param.csv",
package = "packEVPI")
param_list <- packDAMipd::define_parameters(
tp_well_dis_co = packDAMipd::get_parameter_read("tp_well_dis_co",
param_file),
tp_well_dis_in =  packDAMipd::get_parameter_read("tp_well_dis_in",
param_file),
tp_well_dead =  packDAMipd::get_parameter_read("tp_well_dead", param_file),
tp_dis_dead =  packDAMipd::get_parameter_read("tp_dis_dead", param_file),
 tp_dead_dead =  1,
 cost_well_co =  packDAMipd::get_parameter_read("cost_well_co", param_file),
 cost_well_in =  packDAMipd::get_parameter_read("cost_well_in", param_file),
 cost_dis_co =  packDAMipd::get_parameter_read("cost_dis_co", param_file),
 cost_dis_in =  packDAMipd::get_parameter_read("cost_dis_in", param_file),
 utility_dis_co =  packDAMipd::get_parameter_read("utility_dis_co",
 param_file),
 utility_dis_in =  packDAMipd::get_parameter_read("utility_dis_in",
 param_file),
 tp_well_well_co = "1-(tp_well_dis_co + tp_well_dead)",
 tp_well_well_in = "1-(tp_well_dis_in + tp_well_dead)",
 tp_dis_dis_co = "1-( tp_dis_dead)",
 tp_dis_dis_in = "1-( tp_dis_dead)")
 this_markov <- packDAMipd::markov_model(this.strategy, 24, c(1000, 0, 0),
 discount = c(0, 0),method = "half cycle correction", param_list)
 well <- packDAMipd::health_state("well", cost = "cost_well_in", utility = 1)
 disabled <- packDAMipd::health_state("disabled", cost = "cost_dis_in",
 utility = "utility_dis_in")
 dead <- packDAMipd::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 <- packDAMipd::populate_transition_matrix(3, tmat, c("tp_well_well_in",
 "tp_well_dis_in", "tp_well_dead", "tp_dis_dis_in","tp_dis_dead",
 "tp_dead_dead"), colnames(tmat))
 health_states <- packDAMipd::combine_state(well, disabled, dead)
 this.strategy <- packDAMipd::strategy(tm, health_states, "intervention")
 sec_markov <- packDAMipd::markov_model(this.strategy, 24, c(1000, 0, 0),
 discount = c(0, 0), method = "half cycle correction", param_list)
 list_markov <- packDAMipd::combine_markov(list(this_markov, sec_markov))
param_file <- system.file("extdata", "table_param.csv", package = "packEVPI")
colnames_paramdistr  <- c("Param1_name", "Param1_value", "Param2_name",
 "Param2_value")
 names_params_needed <- colnames(list_markov[1, ]$param_matrix)
 names_params_model <- names(list_markov[1, ]$list_param_values)
 params_passed <- list_markov[1, ]$list_param_values
 parameters <- get_all_parameter_list(names_params_needed, names_params_model,
 params_passed, param_file, colnames_paramdistr)

sheejamk/packEVPI documentation built on April 7, 2023, 8:48 a.m.