Compile MCMC sampler using STAN and create analysis object

Usage

create_analysis_obj(
  data_matrix,
  covariates = NULL,
  outcome,
  borrowing,
  treatment,
  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.
covariates: Covariates. Object of class Covariates as output by the function add_covariates().
outcome: Outcome. Object of class Outcome as output by exp_surv_dist(), weib_ph_surv_dist(), or logistic_bin_outcome().
borrowing: Borrowing. Object of class Borrowing as output by borrowing_details().
treatment: Treatment. Object of class Treatment as output by treatment_details().
quiet: logical. Whether to suppress messages (TRUE) or not (FALSE, the default)

Value

Object of class Analysis.

Examples

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