create_tipmap_data: Create data frame ready to use for tipping point analysis

In tipmap: Tipping Point Analysis for Bayesian Dynamic Borrowing

Create data frame ready to use for tipping point analysis

Description

Combines new trial data created by createTargetData(), a posterior distribution created by create_posterior_data() and a robust MAP prior using RBesT::automixfit() and an optional meta-analysis, e.g. created using the meta package, into a data frame needed for the functions tipmap_plot() and get_tipping_point().

Usage

create_tipmap_data(new_trial_data, posterior, map_prior, meta_analysis = NULL)

Arguments

new_trial_data	A data frame containing data on the new trial in the target population. See create_new_trial_data().
posterior	A mixture combining MAP prior and target population. See create_posterior_data().
map_prior	A robust MAP prior created by RBesT::automixfit().
meta_analysis	A data frame containing a meta-analysis of trial(s) to be borrowed from. See createPriorData().

Value

A data frame ready to be used for tipmap_plot() and get_tipping_point()

See Also

create_new_trial_data, create_posterior_data, tipmap_plot, get_tipping_points

Examples

# specify new trial data
new_trial_data <- create_new_trial_data(n_total = 30, est = 1.5, se = 2.1)

# read MAP prior data
map_prior <- load_tipmap_data("tipmapPrior.rds")

# read posterior data
posterior <- load_tipmap_data("tipPost.rds")

tip_dat <- create_tipmap_data(
  new_trial_data = new_trial_data,
  posterior = posterior,
  map_prior = map_prior
)

tipmap documentation built on Aug. 14, 2023, 5:09 p.m.