Compile MCMC sampler using STAN and create analysis object

Usage

create_analysis_obj(
  data_matrix,
  outcome,
  borrowing,
  treatment,
  covariates = NULL,
  quiet = FALSE
)

Arguments

data_matrix: matrix. The data matrix, including all covariates to be adjusted for, all relevant outcome variables, and treatment arm and external control arm flags.
outcome: Outcome. Object of class Outcome as output by outcome_surv_exponential(), outcome_surv_weibull_ph(), or outcome_bin_logistic().
borrowing: Borrowing. Object of class Borrowing as output by borrowing_full(), borrowing_none(), and borrowing_hierarchical_commensurate().
treatment: Treatment. Object of class Treatment as output by treatment_details().
covariates: Covariates. Object of class Covariates as output by the function add_covariates().
quiet: logical. Whether to suppress messages (TRUE) or not (FALSE, the default)

Value

Object of class Analysis.

Examples

if (check_cmdstan()) {
  anls <- create_analysis_obj(
    data_matrix = example_matrix,
    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)
    ),
    covariates = add_covariates(
      covariates = c("cov1", "cov2"),
      priors = prior_normal(0, 1000)
    )
  )
}
#> Inputs look good.
#> Stan program compiled successfully!
#> Ready to go! Now call `mcmc_sample()`.