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EVPPI wrapper function for total population YLLs by sex

call_evppi_sex.Rd

This function gets the ithim results into the correct format and calls the compute_evppi() script to calculate the EVPPIs for all input parameters and required outcomes and scenarios split by sex.

Usage

call_evppi_sex(
  voi_data_all_sex_df,
  parameter_samples,
  outcome_voi_list,
  outcome,
  cities,
  voi_add_sum,
  NSCEN,
  NSAMPLES,
  scenario_names,
  evppi_df
)

Arguments

voi_data_all_sex_df

dataframe containing all outcomes by sex

parameter_samples

table containing all the input parameter variables for the different model runs for all cities

outcome_voi_list

vector detailing the outcomes to be considered in the VoI analysis

outcome

total yll outcome for all outcome age categories per city and scenario and disease combination, also combined city result (sum)

cities

vector of cities

voi_add_sum

if the sum of YLLs across all disease outcomes is to be considered

NSCEN

number of scenarios (not incl. baseline)

NSAMPLES

number of times the model was run for each city

scenario_names

gives the names of the scenarios (incl baseline)

evppi_df

outcome dataframe containing voi analysis for total yll across all age and sex categories

Value

a list containing the following elements:

evppi_ex_df dataframe containing all EVPPI outcomes for all sex categories and all cities

sex_cat vector with both sexes

evppi_city_list_all_sex list where each list entry is a dataframe containing all EvPPI outcomes for all sex categories for one city

Details

The function performs the following steps:

  • create a vector containing the global parameters but not including the emission inventory parameters as they are not independent of each other

  • loop through the cities:

    • extract the city specific parameters (excluding the CO2 and PM emission inventory parameters)

    • loop through the two sexes:

      • extract the outcomes of interest for each scenario using the outcome_voi_list

      • if voi_add_sum == TRUE, calculate the total YLLs by summing across all diseases in the outcome_voi_list - this only makes sense if the diseases in the outcome_voi_list are independent of each other

      • call the compute_evppi() function to calculate the expected values of partially perfect information (EVPPI) for all parameters and diseases of interest

    • if NSAMPLES >= 1000 then also calculate the EVPPI values for the emission inventory parameters by looping through both sexes