Check Data Matrix for Required Columns — check_data_matrix_has

Check that an Analysis object's data_matrix has all the required variables.

Usage

check_data_matrix_has_columns(object)

Arguments

object: Analysis. Object to check.

Value

stop() if some columns are missing.

Examples

anls <- create_analysis_obj(
  data_matrix = example_matrix,
  covariates = add_covariates(
    covariates = c("cov1", "cov2"),
    priors = prior_normal(0, 1000)
  ),
  outcome = outcome_surv_exponential(
    "time",
    "cnsr",
    baseline_prior = prior_normal(0, 1000)
  ),
  borrowing = borrowing_hierarchical_commensurate(
    "ext",
    prior_exponential(.001)
  ),
  treatment = treatment_details(
    "trt",
    prior_normal(0, 1000)
  )
)
#> Inputs look good.
#> Stan program compiled successfully!
#> Ready to go! Now call `mcmc_sample()`.

check_data_matrix_has_columns(anls)