create_analysis_obj: Compile MCMC sampler using STAN and create analysis object

In psborrow2: Bayesian Dynamic Borrowing Analysis and Simulation

Compile MCMC sampler using STAN and create analysis object

Description

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)
    )
  )
}

psborrow2 documentation built on April 4, 2025, 12:37 a.m.