character. Name of time variable column in model matrix
cens_var
character. Name of the censorship variable flag in model matrix
shape_prior
Prior class object for the Weibull shape
parameter. Default is prior_exponential(beta = 0.0001).
baseline_prior
Prior. Object of class Prior
specifying prior distribution for the baseline outcome.
See Details for more information.
weight_var
character. Optional name of variable in model matrix for weighting the log likelihood.
Details
Baseline Prior
The baseline_prior argument specifies the prior distribution for the
baseline log hazard rate. The interpretation of the baseline_prior differs
slightly between borrowing methods selected.
Dynamic borrowing using borrowing_hierarchical_commensurate(): the baseline_prior for Bayesian Dynamic Borrowing
refers to the log hazard rate of the external control arm.
Full borrowing or No borrowing using borrowing_full() or borrowing_none(): the baseline_prior for
these borrowing methods refers to the log hazard rate for the
internal control arm.
See Also
Other outcome models:
outcome_bin_logistic(),
outcome_cont_normal(),
outcome_surv_exponential(),
outcome_surv_pem()