Skip to contents

CaptureTB outpatient visit cost model

unitcost.Rd

This function loads a JAGSModel model object fitted using default covariates and priors, with a total of 30,000 posterior samples. This can be used to predict the total cost of a single outpatient visit at a given facility or facilities via the predict method.

Usage

unitcost()

Value

An object of class JAGSModel.

Details

Note that some covariates are centered. The function prepare_covariates() can be used to transform raw variables using the correct centering values.

See also

JAGSModel

Examples

mod <- unitcost()
#> Multiple outputs detected. Including output-level random effects in model.
new_data <- list(
  log_ID_p_bldgspace = 1,
  logVisits = 6.9,
  logVisitsPP_TB = -1.29,
  primary = TRUE,
  secondary = FALSE,
  tertiary = FALSE,
  urban = FALSE,
  public = TRUE,
  n_services = 3,
  fc_country = "Ethiopia",
  output = "op_treatmentvisit"
)
new_covariates <- prepare_covariates(new_data, mod)
mod$predict(new_covariates, summarised = TRUE)
#> Summary of Posterior Distribution
#> 
#> Observation | Mean |       95% CI
#> ---------------------------------
#> 1           | 2.86 | [1.68, 4.05]