calibrate_meta_analytic: Create meta-analytic predictive prior distributions

In RoBSA: Robust Bayesian Survival Analysis

Create meta-analytic predictive prior distributions

Description

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

Usage

calibrate_meta_analytic(
  datasets,
  distributions = c("exp-aft", "weibull-aft", "lnorm-aft", "llogis-aft", "gamma-aft"),
  prior_mu = prior("cauchy", parameters = list(location = 0, scale = 100)),
  prior_tau = prior("cauchy", parameters = list(location = 0, scale = 10), truncation =
    list(0, Inf)),
  ...
)

Arguments

datasets	list of data.frames containing the historical data. Each data.frame must contain a column named "time" with the survival times and a column named "status" with the censoring status.
distributions	vector of parametric families for which prior distributions ought to be calibrated
prior_mu	prior distribution for the the meta-analytic mean parameter
prior_tau	prior distribution for the the meta-analytic heterogeneity parameter
...	additional parameters to be passed to the meta-analytic function. See BayesTools::JAGS_fit for more details.

Value

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

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