hb_metrics: Legacy function to calculate borrowing metrics

In historicalborrow: Non-Longitudinal Bayesian Historical Borrowing Models

Legacy function to calculate borrowing metrics

Description

Legacy function to calculate historical borrowing metrics using summary output from a fitted borrowing model and analogous summaries from the benchmark models. We recommend hb_ess() instead of hb_metrics(). See the methods vignette in the package for details.

Usage

hb_metrics(borrow, pool, independent)

Arguments

borrow	A data frame returned by hb_summary() for the mixture or hierarchical model.
pool	A data frame returned by hb_summary() for the pooled model.
independent	A data frame returned by hb_summary() for the independent model.

Value

A data frame with borrowing metrics.

Examples

if (!identical(Sys.getenv("HB_TEST", unset = ""), "")) {
data <- hb_sim_independent(n_continuous = 2)$data
mcmc_borrow <- hb_mcmc_hierarchical(
  data,
  n_chains = 1,
  n_adapt = 100,
  n_warmup = 100,
  n_iterations = 200
)
mcmc_pool <- hb_mcmc_pool(
  data,
  n_chains = 1,
  n_adapt = 100,
  n_warmup = 50,
  n_iterations = 50
)
mcmc_independent <- hb_mcmc_independent(
  data,
  n_chains = 1,
  n_adapt = 100,
  n_warmup = 50,
  n_iterations = 50
)
borrow <- hb_summary(mcmc_borrow, data)
pool <- hb_summary(mcmc_pool, data)
independent <- hb_summary(mcmc_independent, data)
hb_metrics(
  borrow = borrow,
  pool = pool,
  independent = independent
)
}

historicalborrow documentation built on Sept. 11, 2024, 9:05 p.m.