calibrate_quartiles: Calibrate prior distributions based on quartiles

In RoBSA: Robust Bayesian Survival Analysis

Calibrate prior distributions based on quartiles

Description

Calibrates prior distributions for parametric survival analysis based on median survival and interquartile range. Returns a list of prior distribution for the intercepts and auxiliary parameters.

Usage

calibrate_quartiles(
  median_t,
  iq_range_t,
  prior_sd = 0.5,
  distributions = c("exp-aft", "weibull-aft", "lnorm-aft", "llogis-aft", "gamma-aft"),
  verbose = FALSE,
  search_bounds1 = c(-100, 100),
  search_bounds2 = c(0 + 0.01, 100)
)

Arguments

median_t	median survival
iq_range_t	interquartile range of the survival
prior_sd	pre-specified standard deviation of the prior distributions (either a single value that is used for both the intercept and auxiliary parameter or a vector where the first value corresponds to the sd for the prior distribution on the intercept and the second value to the sd for the prior distribution on the auxiliary parameter)
distributions	vector of parametric families for which prior distributions ought to be calibrated
verbose	whether debug information be printed
search_bounds1	search boundaries for the intercept parameter
search_bounds2	search boundaries for the auxiliary parameter

Value

returns a list of prior distribution for the intercepts and auxiliary parameters.

Examples

priors <- calibrate_quartiles(median_t = 5, iq_range_t = 10, prior_sd = 0.5)

RoBSA documentation built on April 4, 2025, 5:25 a.m.